ukwa-holdings-summary-report.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# UK Web Archive Holdings Summary Report\n",
    "\n",
    "__WARNING!__ This takes a little while to work...\n",
    "\n",
    "n.b. There is an SQL interface for Solr, but it's not quite powerful enough to do all we need (in particular, grouping by date ranges so we can do financial year reporting). This report depends on pre-generated TrackDB and AWS item data files.\n",
    "\n",
    "## Contents\n",
    "\n",
    "* [Overall Statistics](#overall)\n",
    "* [Statistic by Year](#by-year)\n",
    "* [Statistics by Financial Year](#by-fy)\n",
    "\n",
    "## Overall Statistics <a class=\"anchor\" id=\"overall\"></a>\n",
    "\n",
    "First we load the data and look for duplicate data across the different storage services."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "Found a total of 1,789,943 WARC and crawl log files."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import requests\n",
    "import pandas as pd\n",
    "from trackdb.humanbytes import HumanBytes\n",
    "from IPython.display import display, HTML, FileLink, FileLinks\n",
    "\n",
    "pd.set_option('display.max_rows', 100)\n",
    "\n",
    "# Pick up source locations:\n",
    "trackdb_jsonl = os.environ.get('TRACKDB_LIST_JSONL','trackdb_list.jsonl')\n",
    "aws_jsonl = os.environ.get('AWS_S3_LIST_JSONL','aws_s3_list.jsonl')\n",
    "\n",
    "# Load TrackDB records:\n",
    "df = pd.read_json(trackdb_jsonl, lines=True)\n",
    "\n",
    "# Also load AWS records:\n",
    "aws_df = pd.read_json(aws_jsonl, lines=True)\n",
    "# Filter out non-content files:\n",
    "aws_df  = aws_df[aws_df['kind_s'] != 'unknown']\n",
    "df = pd.concat([df,aws_df], sort=True)\n",
    "\n",
    "# Set up timestamp:\n",
    "df['timestamp_dt']= pd.to_datetime(df['timestamp_dt'])\n",
    "total_records = len(df)\n",
    "\n",
    "# Force integers:\n",
    "df['file_size_l'] = df['file_size_l'].fillna(0)\n",
    "df['file_size_l'] = df['file_size_l'].apply(int)\n",
    "\n",
    "display(HTML(f\"Found a total of {total_records:,} WARC and crawl log files.\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "Found 1,786,441 unique files (based on file path). This means there are 3,502 files duplicated across storage systems."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Dataframe of all unique paths (drop others for paths appearing in more than one 'fresh' TrackDB record):\n",
    "dfu = df.drop_duplicates(subset=['file_path_s']).drop(columns=['file_path_s'])\n",
    "\n",
    "unique_records = len(dfu)\n",
    "\n",
    "display(HTML(f\"Found {unique_records:,} unique files (based on file path). This means there are {(total_records-unique_records):,} files duplicated across storage systems.\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following table shows the most recent WARCs for each data store, along with the associated timestamp. This can be used to check the source data for this report is up to date."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>store</th>\n",
       "      <th>file_path_s</th>\n",
       "      <th>kind_s</th>\n",
       "      <th>timestamp_dt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>aws_s3</td>\n",
       "      <td>/heritrix/output/dc2022/20221129124044/warcs/BL-NPLD-20221231213839902-107742-105~npld-dc-heritrix3-worker-1~8443.warc.gz</td>\n",
       "      <td>warcs</td>\n",
       "      <td>2022-12-31 21:38:39.902000+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>h020</td>\n",
       "      <td>/heritrix/output/frequent-npld/20211105125651/warcs/BL-NPLD-WEBRENDER-frequent-npld-20211105125651-20211219233713621-25721-uvbemtd1.warc.gz</td>\n",
       "      <td>warcs</td>\n",
       "      <td>2021-12-19 23:37:13.621000+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>h3</td>\n",
       "      <td>/heritrix/output/frequent-npld/20221216004208/warcs/BL-NPLD-WEBRENDER-frequent-npld-20221216004208-20230124065416678-07533-16qo5sjg.warc.gz</td>\n",
       "      <td>warcs</td>\n",
       "      <td>2023-01-24 06:54:16.678000+00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    store  \\\n",
       "0  aws_s3   \n",
       "1  h020     \n",
       "2  h3       \n",
       "\n",
       "                                                                                                                                   file_path_s  \\\n",
       "0  /heritrix/output/dc2022/20221129124044/warcs/BL-NPLD-20221231213839902-107742-105~npld-dc-heritrix3-worker-1~8443.warc.gz                     \n",
       "1  /heritrix/output/frequent-npld/20211105125651/warcs/BL-NPLD-WEBRENDER-frequent-npld-20211105125651-20211219233713621-25721-uvbemtd1.warc.gz   \n",
       "2  /heritrix/output/frequent-npld/20221216004208/warcs/BL-NPLD-WEBRENDER-frequent-npld-20221216004208-20230124065416678-07533-16qo5sjg.warc.gz   \n",
       "\n",
       "  kind_s                     timestamp_dt  \n",
       "0  warcs 2022-12-31 21:38:39.902000+00:00  \n",
       "1  warcs 2021-12-19 23:37:13.621000+00:00  \n",
       "2  warcs 2023-01-24 06:54:16.678000+00:00  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_colwidth', 1024)\n",
    "# Now we look for the most recent WARC files:\n",
    "dflw = df.filter(items=['hdfs_service_id_s', 'file_path_s', 'kind_s', 'timestamp_dt'], axis=1)\n",
    "dflw = dflw.loc[dflw['kind_s'] == 'warcs'].sort_values(['timestamp_dt'],ascending=False).groupby('hdfs_service_id_s').first()\n",
    "dflw = dflw.reset_index().rename(columns={\n",
    "    'hdfs_service_id_s': 'store',\n",
    "})\n",
    "dflw"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Statistics by Year <a class=\"anchor\" id=\"by-year\"></a>\n",
    "\n",
    "This table summarises our overall totals for the different kinds of data we hold.\n",
    "\n",
    "### Overall totals by year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>file_count</th>\n",
       "      <th>size_bytes</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>5128</td>\n",
       "      <td>889707367400</td>\n",
       "      <td>889.7 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011</td>\n",
       "      <td>152823</td>\n",
       "      <td>9752750101708</td>\n",
       "      <td>9.8 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012</td>\n",
       "      <td>62693</td>\n",
       "      <td>5155656912300</td>\n",
       "      <td>5.2 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>99566</td>\n",
       "      <td>44626484557524</td>\n",
       "      <td>44.6 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>111345</td>\n",
       "      <td>74965482998137</td>\n",
       "      <td>75.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2015</td>\n",
       "      <td>131242</td>\n",
       "      <td>92377023633565</td>\n",
       "      <td>92.4 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2016</td>\n",
       "      <td>136996</td>\n",
       "      <td>131955902382200</td>\n",
       "      <td>132.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017</td>\n",
       "      <td>135265</td>\n",
       "      <td>104515586779827</td>\n",
       "      <td>104.5 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018</td>\n",
       "      <td>139734</td>\n",
       "      <td>120955715797493</td>\n",
       "      <td>121.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019</td>\n",
       "      <td>187203</td>\n",
       "      <td>169359134779426</td>\n",
       "      <td>169.4 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020</td>\n",
       "      <td>157614</td>\n",
       "      <td>154867303109935</td>\n",
       "      <td>154.9 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2021</td>\n",
       "      <td>234377</td>\n",
       "      <td>236937217445920</td>\n",
       "      <td>236.9 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2022</td>\n",
       "      <td>225159</td>\n",
       "      <td>225102995109197</td>\n",
       "      <td>225.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2023</td>\n",
       "      <td>7295</td>\n",
       "      <td>7345692743440</td>\n",
       "      <td>7.3 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td></td>\n",
       "      <td>1786440</td>\n",
       "      <td>1378806653718072</td>\n",
       "      <td>1.4 PB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       year  file_count        size_bytes      size\n",
       "0      2010        5128      889707367400  889.7 GB\n",
       "1      2011      152823     9752750101708    9.8 TB\n",
       "2      2012       62693     5155656912300    5.2 TB\n",
       "3      2013       99566    44626484557524   44.6 TB\n",
       "4      2014      111345    74965482998137   75.0 TB\n",
       "5      2015      131242    92377023633565   92.4 TB\n",
       "6      2016      136996   131955902382200  132.0 TB\n",
       "7      2017      135265   104515586779827  104.5 TB\n",
       "8      2018      139734   120955715797493  121.0 TB\n",
       "9      2019      187203   169359134779426  169.4 TB\n",
       "10     2020      157614   154867303109935  154.9 TB\n",
       "11     2021      234377   236937217445920  236.9 TB\n",
       "12     2022      225159   225102995109197  225.1 TB\n",
       "13     2023        7295     7345692743440    7.3 TB\n",
       "Total           1786440  1378806653718072    1.4 PB"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Download the data from this table here: <a href='totals_by_year.csv' target='_blank'>totals_by_year.csv</a><br>"
      ],
      "text/plain": [
       "/home/anj/ukwa-notebook-apps/totals_by_year.csv"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import display\n",
    "\n",
    "def show_table_and_dl(df, slug):\n",
    "    # Shift to standard Column Names\n",
    "    df = df.rename(columns={\n",
    "        'timestamp_dt': 'year',\n",
    "        'collection_s': 'collection',\n",
    "        'stream_s': 'stream',\n",
    "        'kind_s': 'kind',\n",
    "        'size': 'size_bytes',\n",
    "        'count': 'file_count',\n",
    "        'hdfs_service_id_s': 'store'\n",
    "    })\n",
    "\n",
    "    # Add a Total:\n",
    "    df.loc['Total']= df.sum(numeric_only=True)\n",
    "    \n",
    "    # Replace NaNs\n",
    "    df = df.fillna('')\n",
    "\n",
    "    # Clean up size formatting:\n",
    "    df['size'] = df['size_bytes'].apply(lambda x: HumanBytes.format(x, True))\n",
    "    df['size_bytes'] = df['size_bytes'].apply(int)\n",
    "    df['file_count'] = df['file_count'].apply(int)\n",
    "    \n",
    "    # Also make the data available for download:\n",
    "    csv_file = f'{slug}.csv'\n",
    "    df.to_csv(csv_file, index=False)\n",
    "    dl = FileLink(csv_file, result_html_prefix='Download the data from this table here: ')\n",
    "    display(df,dl)\n",
    "\n",
    "#tots = dfu.groupby([pd.Grouper(key='timestamp_dt', freq=\"A\"), 'collection_s', 'stream_s', 'hdfs_service_id_s', 'kind_s']).agg(count=('file_size_l', 'count'), size=('file_size_l', 'sum'))\n",
    "tots = dfu.groupby([pd.Grouper(key='timestamp_dt', freq=\"A\")]).agg(count=('file_size_l', 'count'), size=('file_size_l', 'sum'))\n",
    "tots = tots.reset_index()\n",
    "\n",
    "# Clip year:\n",
    "tots['timestamp_dt'] = tots['timestamp_dt'].dt.year.apply(lambda x: str(x))\n",
    "\n",
    "# Show table and downloader:\n",
    "show_table_and_dl(tots, 'totals_by_year')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Totals by Year & Collection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>collection</th>\n",
       "      <th>file_count</th>\n",
       "      <th>size_bytes</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>selective</td>\n",
       "      <td>5128</td>\n",
       "      <td>889707367400</td>\n",
       "      <td>889.7 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011</td>\n",
       "      <td>selective</td>\n",
       "      <td>152823</td>\n",
       "      <td>9752750101708</td>\n",
       "      <td>9.8 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012</td>\n",
       "      <td>selective</td>\n",
       "      <td>62693</td>\n",
       "      <td>5155656912300</td>\n",
       "      <td>5.2 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>npld</td>\n",
       "      <td>39719</td>\n",
       "      <td>39651261733311</td>\n",
       "      <td>39.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>selective</td>\n",
       "      <td>59847</td>\n",
       "      <td>4975222824213</td>\n",
       "      <td>5.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2014</td>\n",
       "      <td>npld</td>\n",
       "      <td>77222</td>\n",
       "      <td>71825678300361</td>\n",
       "      <td>71.8 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2014</td>\n",
       "      <td>selective</td>\n",
       "      <td>34123</td>\n",
       "      <td>3139804697776</td>\n",
       "      <td>3.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2015</td>\n",
       "      <td>npld</td>\n",
       "      <td>93216</td>\n",
       "      <td>90102310863233</td>\n",
       "      <td>90.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2015</td>\n",
       "      <td>selective</td>\n",
       "      <td>38026</td>\n",
       "      <td>2274712770332</td>\n",
       "      <td>2.3 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>130400</td>\n",
       "      <td>131562200904391</td>\n",
       "      <td>131.6 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2016</td>\n",
       "      <td>selective</td>\n",
       "      <td>6596</td>\n",
       "      <td>393701477809</td>\n",
       "      <td>393.7 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>135265</td>\n",
       "      <td>104515586779827</td>\n",
       "      <td>104.5 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>139734</td>\n",
       "      <td>120955715797493</td>\n",
       "      <td>121.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>187203</td>\n",
       "      <td>169359134779426</td>\n",
       "      <td>169.4 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>157614</td>\n",
       "      <td>154867303109935</td>\n",
       "      <td>154.9 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>234377</td>\n",
       "      <td>236937217445920</td>\n",
       "      <td>236.9 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>225159</td>\n",
       "      <td>225102995109197</td>\n",
       "      <td>225.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2023</td>\n",
       "      <td>npld</td>\n",
       "      <td>7295</td>\n",
       "      <td>7345692743440</td>\n",
       "      <td>7.3 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1786440</td>\n",
       "      <td>1378806653718072</td>\n",
       "      <td>1.4 PB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       year collection  file_count        size_bytes      size\n",
       "0      2010  selective        5128      889707367400  889.7 GB\n",
       "1      2011  selective      152823     9752750101708    9.8 TB\n",
       "2      2012  selective       62693     5155656912300    5.2 TB\n",
       "3      2013       npld       39719    39651261733311   39.7 TB\n",
       "4      2013  selective       59847     4975222824213    5.0 TB\n",
       "5      2014       npld       77222    71825678300361   71.8 TB\n",
       "6      2014  selective       34123     3139804697776    3.1 TB\n",
       "7      2015       npld       93216    90102310863233   90.1 TB\n",
       "8      2015  selective       38026     2274712770332    2.3 TB\n",
       "9      2016       npld      130400   131562200904391  131.6 TB\n",
       "10     2016  selective        6596      393701477809  393.7 GB\n",
       "11     2017       npld      135265   104515586779827  104.5 TB\n",
       "12     2018       npld      139734   120955715797493  121.0 TB\n",
       "13     2019       npld      187203   169359134779426  169.4 TB\n",
       "14     2020       npld      157614   154867303109935  154.9 TB\n",
       "15     2021       npld      234377   236937217445920  236.9 TB\n",
       "16     2022       npld      225159   225102995109197  225.1 TB\n",
       "17     2023       npld        7295     7345692743440    7.3 TB\n",
       "Total                      1786440  1378806653718072    1.4 PB"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Download the data from this table here: <a href='totals_by_year_collection.csv' target='_blank'>totals_by_year_collection.csv</a><br>"
      ],
      "text/plain": [
       "/home/anj/ukwa-notebook-apps/totals_by_year_collection.csv"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#tots = dfu.groupby([pd.Grouper(key='timestamp_dt', freq=\"A\"), 'collection_s', 'stream_s', 'hdfs_service_id_s', 'kind_s']).agg(count=('file_size_l', 'count'), size=('file_size_l', 'sum'))\n",
    "tots = dfu.groupby([pd.Grouper(key='timestamp_dt', freq=\"A\"), 'collection_s']).agg(count=('file_size_l', 'count'), size=('file_size_l', 'sum'))\n",
    "tots = tots.reset_index()\n",
    "\n",
    "# Clip year:\n",
    "tots['timestamp_dt'] = tots['timestamp_dt'].dt.year.apply(lambda x: str(x))\n",
    "\n",
    "# Show table and downloader:\n",
    "show_table_and_dl(tots, 'totals_by_year_collection')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Totals by Year, Collection, Stream, Store & Kind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>collection</th>\n",
       "      <th>stream</th>\n",
       "      <th>store</th>\n",
       "      <th>kind</th>\n",
       "      <th>file_count</th>\n",
       "      <th>size_bytes</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>50</td>\n",
       "      <td>16174178</td>\n",
       "      <td>16.2 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>5078</td>\n",
       "      <td>889691193222</td>\n",
       "      <td>889.7 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>30896</td>\n",
       "      <td>70177720850</td>\n",
       "      <td>70.2 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>121927</td>\n",
       "      <td>9682572380858</td>\n",
       "      <td>9.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>11337</td>\n",
       "      <td>29180359746</td>\n",
       "      <td>29.2 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2012</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>51356</td>\n",
       "      <td>5126476552554</td>\n",
       "      <td>5.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2013</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>9</td>\n",
       "      <td>497880630017</td>\n",
       "      <td>497.9 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2013</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>10</td>\n",
       "      <td>4378472582</td>\n",
       "      <td>4.4 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2013</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>33102</td>\n",
       "      <td>33902836541889</td>\n",
       "      <td>33.9 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2013</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>17</td>\n",
       "      <td>99041071</td>\n",
       "      <td>99.0 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2013</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>6581</td>\n",
       "      <td>5246067047752</td>\n",
       "      <td>5.2 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2013</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>9853</td>\n",
       "      <td>30828782244</td>\n",
       "      <td>30.8 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2013</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>49994</td>\n",
       "      <td>4944394041969</td>\n",
       "      <td>4.9 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2014</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>228</td>\n",
       "      <td>4882231936</td>\n",
       "      <td>4.9 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2014</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>61196</td>\n",
       "      <td>62133135017950</td>\n",
       "      <td>62.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2014</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>11</td>\n",
       "      <td>34269049</td>\n",
       "      <td>34.3 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2014</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>15787</td>\n",
       "      <td>9687626781426</td>\n",
       "      <td>9.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2014</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>5065</td>\n",
       "      <td>17389874737</td>\n",
       "      <td>17.4 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2014</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>29058</td>\n",
       "      <td>3122414823039</td>\n",
       "      <td>3.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2015</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>109</td>\n",
       "      <td>235613102166</td>\n",
       "      <td>235.6 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2015</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>199</td>\n",
       "      <td>4570058043</td>\n",
       "      <td>4.6 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2015</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>74237</td>\n",
       "      <td>75488235762146</td>\n",
       "      <td>75.5 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2015</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>36</td>\n",
       "      <td>271945467</td>\n",
       "      <td>271.9 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2015</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>18635</td>\n",
       "      <td>14373619995411</td>\n",
       "      <td>14.4 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2015</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>7945</td>\n",
       "      <td>15662303216</td>\n",
       "      <td>15.7 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2015</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>30081</td>\n",
       "      <td>2259050467116</td>\n",
       "      <td>2.3 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>587</td>\n",
       "      <td>1021393765281</td>\n",
       "      <td>1.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>237</td>\n",
       "      <td>8012152161</td>\n",
       "      <td>8.0 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>102141</td>\n",
       "      <td>103798783257500</td>\n",
       "      <td>103.8 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>92</td>\n",
       "      <td>40202387198</td>\n",
       "      <td>40.2 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>125</td>\n",
       "      <td>2170071165</td>\n",
       "      <td>2.2 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>27212</td>\n",
       "      <td>26691147872029</td>\n",
       "      <td>26.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>webrecorder</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>6</td>\n",
       "      <td>491399057</td>\n",
       "      <td>491.4 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2016</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>1372</td>\n",
       "      <td>2211062877</td>\n",
       "      <td>2.2 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2016</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>5224</td>\n",
       "      <td>391490414932</td>\n",
       "      <td>391.5 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>254</td>\n",
       "      <td>827631587106</td>\n",
       "      <td>827.6 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>154</td>\n",
       "      <td>4444901826</td>\n",
       "      <td>4.4 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>76079</td>\n",
       "      <td>76973045845589</td>\n",
       "      <td>77.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>18035</td>\n",
       "      <td>933573121920</td>\n",
       "      <td>933.6 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>346</td>\n",
       "      <td>119883019</td>\n",
       "      <td>119.9 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>40397</td>\n",
       "      <td>25776771440367</td>\n",
       "      <td>25.8 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>2109</td>\n",
       "      <td>1417051338354</td>\n",
       "      <td>1.4 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>445</td>\n",
       "      <td>2075196719</td>\n",
       "      <td>2.1 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>59420</td>\n",
       "      <td>57584278800929</td>\n",
       "      <td>57.6 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>5768</td>\n",
       "      <td>1273256843460</td>\n",
       "      <td>1.3 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>707</td>\n",
       "      <td>255134402</td>\n",
       "      <td>255.1 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>71285</td>\n",
       "      <td>60678798483629</td>\n",
       "      <td>60.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>451</td>\n",
       "      <td>998109935920</td>\n",
       "      <td>998.1 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>139</td>\n",
       "      <td>1771940785</td>\n",
       "      <td>1.8 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>70727</td>\n",
       "      <td>62704803095201</td>\n",
       "      <td>62.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>4924</td>\n",
       "      <td>3306036343595</td>\n",
       "      <td>3.3 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>1152</td>\n",
       "      <td>244227036</td>\n",
       "      <td>244.2 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>109693</td>\n",
       "      <td>102332853678911</td>\n",
       "      <td>102.3 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>20</td>\n",
       "      <td>14177092595</td>\n",
       "      <td>14.2 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>webrecorder</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>97</td>\n",
       "      <td>1138465383</td>\n",
       "      <td>1.1 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>122</td>\n",
       "      <td>1067608520089</td>\n",
       "      <td>1.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>viral</td>\n",
       "      <td>105</td>\n",
       "      <td>1914939285</td>\n",
       "      <td>1.9 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>97540</td>\n",
       "      <td>94105431547498</td>\n",
       "      <td>94.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>14</td>\n",
       "      <td>95071921657</td>\n",
       "      <td>95.1 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>4</td>\n",
       "      <td>21493171</td>\n",
       "      <td>21.5 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>1020</td>\n",
       "      <td>2352251432914</td>\n",
       "      <td>2.4 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>105</td>\n",
       "      <td>64387232</td>\n",
       "      <td>64.4 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>58703</td>\n",
       "      <td>57243285631036</td>\n",
       "      <td>57.2 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>webrecorder</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>1</td>\n",
       "      <td>1653237053</td>\n",
       "      <td>1.7 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>69</td>\n",
       "      <td>111488149755</td>\n",
       "      <td>111.5 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>viral</td>\n",
       "      <td>96</td>\n",
       "      <td>1821826003</td>\n",
       "      <td>1.8 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>76094</td>\n",
       "      <td>75658374600860</td>\n",
       "      <td>75.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>519</td>\n",
       "      <td>2249613390697</td>\n",
       "      <td>2.2 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>84</td>\n",
       "      <td>130638583</td>\n",
       "      <td>130.6 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>146503</td>\n",
       "      <td>147727440936103</td>\n",
       "      <td>147.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>11</td>\n",
       "      <td>113465607726</td>\n",
       "      <td>113.5 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>viral</td>\n",
       "      <td>2</td>\n",
       "      <td>1786801</td>\n",
       "      <td>1.8 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>10998</td>\n",
       "      <td>11074796503534</td>\n",
       "      <td>11.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>webrecorder</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>1</td>\n",
       "      <td>84005858</td>\n",
       "      <td>84.0 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>26</td>\n",
       "      <td>19155630028</td>\n",
       "      <td>19.2 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>viral</td>\n",
       "      <td>104</td>\n",
       "      <td>2067502501</td>\n",
       "      <td>2.1 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>108106</td>\n",
       "      <td>106638546143768</td>\n",
       "      <td>106.6 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>305</td>\n",
       "      <td>2740058175535</td>\n",
       "      <td>2.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>260</td>\n",
       "      <td>537439199771</td>\n",
       "      <td>537.4 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>viral</td>\n",
       "      <td>94</td>\n",
       "      <td>33918738</td>\n",
       "      <td>33.9 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>116264</td>\n",
       "      <td>115165694538856</td>\n",
       "      <td>115.2 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>2023</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>25</td>\n",
       "      <td>178833044295</td>\n",
       "      <td>178.8 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>2023</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>24</td>\n",
       "      <td>8907614</td>\n",
       "      <td>8.9 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>2023</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>viral</td>\n",
       "      <td>8</td>\n",
       "      <td>294450</td>\n",
       "      <td>294.4 kB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>2023</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>7238</td>\n",
       "      <td>7166850497081</td>\n",
       "      <td>7.2 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1786440</td>\n",
       "      <td>1378806653718072</td>\n",
       "      <td>1.4 PB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       year collection       stream   store        kind  file_count  \\\n",
       "0      2010  selective    selective    h020  crawl-logs          50   \n",
       "1      2010  selective    selective    h020       warcs        5078   \n",
       "2      2011  selective    selective    h020  crawl-logs       30896   \n",
       "3      2011  selective    selective    h020       warcs      121927   \n",
       "4      2012  selective    selective    h020  crawl-logs       11337   \n",
       "5      2012  selective    selective    h020       warcs       51356   \n",
       "6      2013       npld       domain    h020  crawl-logs           9   \n",
       "7      2013       npld       domain    h020       viral          10   \n",
       "8      2013       npld       domain    h020       warcs       33102   \n",
       "9      2013       npld     frequent    h020       viral          17   \n",
       "10     2013       npld     frequent    h020       warcs        6581   \n",
       "11     2013  selective    selective    h020  crawl-logs        9853   \n",
       "12     2013  selective    selective    h020       warcs       49994   \n",
       "13     2014       npld       domain    h020       viral         228   \n",
       "14     2014       npld       domain    h020       warcs       61196   \n",
       "15     2014       npld     frequent    h020       viral          11   \n",
       "16     2014       npld     frequent    h020       warcs       15787   \n",
       "17     2014  selective    selective    h020  crawl-logs        5065   \n",
       "18     2014  selective    selective    h020       warcs       29058   \n",
       "19     2015       npld       domain    h020  crawl-logs         109   \n",
       "20     2015       npld       domain    h020       viral         199   \n",
       "21     2015       npld       domain    h020       warcs       74237   \n",
       "22     2015       npld     frequent    h020       viral          36   \n",
       "23     2015       npld     frequent    h020       warcs       18635   \n",
       "24     2015  selective    selective    h020  crawl-logs        7945   \n",
       "25     2015  selective    selective    h020       warcs       30081   \n",
       "26     2016       npld       domain    h020  crawl-logs         587   \n",
       "27     2016       npld       domain    h020       viral         237   \n",
       "28     2016       npld       domain    h020       warcs      102141   \n",
       "29     2016       npld     frequent    h020  crawl-logs          92   \n",
       "30     2016       npld     frequent    h020       viral         125   \n",
       "31     2016       npld     frequent    h020       warcs       27212   \n",
       "32     2016       npld  webrecorder    h020       warcs           6   \n",
       "33     2016  selective    selective    h020  crawl-logs        1372   \n",
       "34     2016  selective    selective    h020       warcs        5224   \n",
       "35     2017       npld       domain    h020  crawl-logs         254   \n",
       "36     2017       npld       domain    h020       viral         154   \n",
       "37     2017       npld       domain    h020       warcs       76079   \n",
       "38     2017       npld     frequent    h020  crawl-logs       18035   \n",
       "39     2017       npld     frequent    h020       viral         346   \n",
       "40     2017       npld     frequent    h020       warcs       40397   \n",
       "41     2018       npld       domain    h020  crawl-logs        2109   \n",
       "42     2018       npld       domain    h020       viral         445   \n",
       "43     2018       npld       domain    h020       warcs       59420   \n",
       "44     2018       npld     frequent    h020  crawl-logs        5768   \n",
       "45     2018       npld     frequent    h020       viral         707   \n",
       "46     2018       npld     frequent    h020       warcs       71285   \n",
       "47     2019       npld       domain    h020  crawl-logs         451   \n",
       "48     2019       npld       domain    h020       viral         139   \n",
       "49     2019       npld       domain    h020       warcs       70727   \n",
       "50     2019       npld     frequent    h020  crawl-logs        4924   \n",
       "51     2019       npld     frequent    h020       viral        1152   \n",
       "52     2019       npld     frequent    h020       warcs      109693   \n",
       "53     2019       npld     frequent      h3       warcs          20   \n",
       "54     2019       npld  webrecorder    h020       warcs          97   \n",
       "55     2020       npld       domain  aws_s3  crawl-logs         122   \n",
       "56     2020       npld       domain  aws_s3       viral         105   \n",
       "57     2020       npld       domain  aws_s3       warcs       97540   \n",
       "58     2020       npld       domain    h020  crawl-logs          14   \n",
       "59     2020       npld       domain    h020       viral           4   \n",
       "60     2020       npld     frequent    h020  crawl-logs        1020   \n",
       "61     2020       npld     frequent    h020       viral         105   \n",
       "62     2020       npld     frequent    h020       warcs       58703   \n",
       "63     2020       npld  webrecorder    h020       warcs           1   \n",
       "64     2021       npld       domain  aws_s3  crawl-logs          69   \n",
       "65     2021       npld       domain  aws_s3       viral          96   \n",
       "66     2021       npld       domain  aws_s3       warcs       76094   \n",
       "67     2021       npld     frequent    h020  crawl-logs         519   \n",
       "68     2021       npld     frequent    h020       viral          84   \n",
       "69     2021       npld     frequent    h020       warcs      146503   \n",
       "70     2021       npld     frequent      h3  crawl-logs          11   \n",
       "71     2021       npld     frequent      h3       viral           2   \n",
       "72     2021       npld     frequent      h3       warcs       10998   \n",
       "73     2021       npld  webrecorder    h020       warcs           1   \n",
       "74     2022       npld       domain  aws_s3  crawl-logs          26   \n",
       "75     2022       npld       domain  aws_s3       viral         104   \n",
       "76     2022       npld       domain  aws_s3       warcs      108106   \n",
       "77     2022       npld     frequent    h020  crawl-logs         305   \n",
       "78     2022       npld     frequent      h3  crawl-logs         260   \n",
       "79     2022       npld     frequent      h3       viral          94   \n",
       "80     2022       npld     frequent      h3       warcs      116264   \n",
       "81     2023       npld     frequent    h020  crawl-logs          25   \n",
       "82     2023       npld     frequent      h3  crawl-logs          24   \n",
       "83     2023       npld     frequent      h3       viral           8   \n",
       "84     2023       npld     frequent      h3       warcs        7238   \n",
       "Total                                                       1786440   \n",
       "\n",
       "             size_bytes      size  \n",
       "0              16174178   16.2 MB  \n",
       "1          889691193222  889.7 GB  \n",
       "2           70177720850   70.2 GB  \n",
       "3         9682572380858    9.7 TB  \n",
       "4           29180359746   29.2 GB  \n",
       "5         5126476552554    5.1 TB  \n",
       "6          497880630017  497.9 GB  \n",
       "7            4378472582    4.4 GB  \n",
       "8        33902836541889   33.9 TB  \n",
       "9              99041071   99.0 MB  \n",
       "10        5246067047752    5.2 TB  \n",
       "11          30828782244   30.8 GB  \n",
       "12        4944394041969    4.9 TB  \n",
       "13           4882231936    4.9 GB  \n",
       "14       62133135017950   62.1 TB  \n",
       "15             34269049   34.3 MB  \n",
       "16        9687626781426    9.7 TB  \n",
       "17          17389874737   17.4 GB  \n",
       "18        3122414823039    3.1 TB  \n",
       "19         235613102166  235.6 GB  \n",
       "20           4570058043    4.6 GB  \n",
       "21       75488235762146   75.5 TB  \n",
       "22            271945467  271.9 MB  \n",
       "23       14373619995411   14.4 TB  \n",
       "24          15662303216   15.7 GB  \n",
       "25        2259050467116    2.3 TB  \n",
       "26        1021393765281    1.0 TB  \n",
       "27           8012152161    8.0 GB  \n",
       "28      103798783257500  103.8 TB  \n",
       "29          40202387198   40.2 GB  \n",
       "30           2170071165    2.2 GB  \n",
       "31       26691147872029   26.7 TB  \n",
       "32            491399057  491.4 MB  \n",
       "33           2211062877    2.2 GB  \n",
       "34         391490414932  391.5 GB  \n",
       "35         827631587106  827.6 GB  \n",
       "36           4444901826    4.4 GB  \n",
       "37       76973045845589   77.0 TB  \n",
       "38         933573121920  933.6 GB  \n",
       "39            119883019  119.9 MB  \n",
       "40       25776771440367   25.8 TB  \n",
       "41        1417051338354    1.4 TB  \n",
       "42           2075196719    2.1 GB  \n",
       "43       57584278800929   57.6 TB  \n",
       "44        1273256843460    1.3 TB  \n",
       "45            255134402  255.1 MB  \n",
       "46       60678798483629   60.7 TB  \n",
       "47         998109935920  998.1 GB  \n",
       "48           1771940785    1.8 GB  \n",
       "49       62704803095201   62.7 TB  \n",
       "50        3306036343595    3.3 TB  \n",
       "51            244227036  244.2 MB  \n",
       "52      102332853678911  102.3 TB  \n",
       "53          14177092595   14.2 GB  \n",
       "54           1138465383    1.1 GB  \n",
       "55        1067608520089    1.1 TB  \n",
       "56           1914939285    1.9 GB  \n",
       "57       94105431547498   94.1 TB  \n",
       "58          95071921657   95.1 GB  \n",
       "59             21493171   21.5 MB  \n",
       "60        2352251432914    2.4 TB  \n",
       "61             64387232   64.4 MB  \n",
       "62       57243285631036   57.2 TB  \n",
       "63           1653237053    1.7 GB  \n",
       "64         111488149755  111.5 GB  \n",
       "65           1821826003    1.8 GB  \n",
       "66       75658374600860   75.7 TB  \n",
       "67        2249613390697    2.2 TB  \n",
       "68            130638583  130.6 MB  \n",
       "69      147727440936103  147.7 TB  \n",
       "70         113465607726  113.5 GB  \n",
       "71              1786801    1.8 MB  \n",
       "72       11074796503534   11.1 TB  \n",
       "73             84005858   84.0 MB  \n",
       "74          19155630028   19.2 GB  \n",
       "75           2067502501    2.1 GB  \n",
       "76      106638546143768  106.6 TB  \n",
       "77        2740058175535    2.7 TB  \n",
       "78         537439199771  537.4 GB  \n",
       "79             33918738   33.9 MB  \n",
       "80      115165694538856  115.2 TB  \n",
       "81         178833044295  178.8 GB  \n",
       "82              8907614    8.9 MB  \n",
       "83               294450  294.4 kB  \n",
       "84        7166850497081    7.2 TB  \n",
       "Total  1378806653718072    1.4 PB  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Download the data from this table here: <a href='totals_by_year_collection_stream_store_kind.csv' target='_blank'>totals_by_year_collection_stream_store_kind.csv</a><br>"
      ],
      "text/plain": [
       "/home/anj/ukwa-notebook-apps/totals_by_year_collection_stream_store_kind.csv"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tots = dfu.groupby([pd.Grouper(key='timestamp_dt', freq=\"A\"), 'collection_s', 'stream_s', 'hdfs_service_id_s', 'kind_s']).agg(count=('file_size_l', 'count'), size=('file_size_l', 'sum'))\n",
    "tots = tots.reset_index()\n",
    "\n",
    "# Clip year:\n",
    "tots['timestamp_dt'] = tots['timestamp_dt'].dt.year.apply(lambda x: str(x))\n",
    "\n",
    "# Show table and downloader:\n",
    "show_table_and_dl(tots, 'totals_by_year_collection_stream_store_kind')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Statistics by Financial Year <a class=\"anchor\" id=\"by-fy\"></a>\n",
    "\n",
    "The same data, but aggregating by financial year.\n",
    "\n",
    "### Totals by Financial Year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>file_count</th>\n",
       "      <th>size_bytes</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-2011</td>\n",
       "      <td>113204</td>\n",
       "      <td>7816892967770</td>\n",
       "      <td>7.8 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011-2012</td>\n",
       "      <td>59960</td>\n",
       "      <td>4030906309550</td>\n",
       "      <td>4.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-2013</td>\n",
       "      <td>79156</td>\n",
       "      <td>6721789281245</td>\n",
       "      <td>6.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-2014</td>\n",
       "      <td>81051</td>\n",
       "      <td>44989409025831</td>\n",
       "      <td>45.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-2015</td>\n",
       "      <td>114626</td>\n",
       "      <td>75189816802413</td>\n",
       "      <td>75.2 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2015-2016</td>\n",
       "      <td>129525</td>\n",
       "      <td>97636439682175</td>\n",
       "      <td>97.6 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2016-2017</td>\n",
       "      <td>144414</td>\n",
       "      <td>132324447179156</td>\n",
       "      <td>132.3 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017-2018</td>\n",
       "      <td>121999</td>\n",
       "      <td>100724574184843</td>\n",
       "      <td>100.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018-2019</td>\n",
       "      <td>153246</td>\n",
       "      <td>135805661816176</td>\n",
       "      <td>135.8 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-2020</td>\n",
       "      <td>178575</td>\n",
       "      <td>162784476670294</td>\n",
       "      <td>162.8 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020-2021</td>\n",
       "      <td>171972</td>\n",
       "      <td>169872606455107</td>\n",
       "      <td>169.9 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2021-2022</td>\n",
       "      <td>243340</td>\n",
       "      <td>246553603363134</td>\n",
       "      <td>246.6 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2022-2023</td>\n",
       "      <td>195372</td>\n",
       "      <td>194356029980378</td>\n",
       "      <td>194.4 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td></td>\n",
       "      <td>1786440</td>\n",
       "      <td>1378806653718072</td>\n",
       "      <td>1.4 PB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            year  file_count        size_bytes      size\n",
       "0      2010-2011      113204     7816892967770    7.8 TB\n",
       "1      2011-2012       59960     4030906309550    4.0 TB\n",
       "2      2012-2013       79156     6721789281245    6.7 TB\n",
       "3      2013-2014       81051    44989409025831   45.0 TB\n",
       "4      2014-2015      114626    75189816802413   75.2 TB\n",
       "5      2015-2016      129525    97636439682175   97.6 TB\n",
       "6      2016-2017      144414   132324447179156  132.3 TB\n",
       "7      2017-2018      121999   100724574184843  100.7 TB\n",
       "8      2018-2019      153246   135805661816176  135.8 TB\n",
       "9      2019-2020      178575   162784476670294  162.8 TB\n",
       "10     2020-2021      171972   169872606455107  169.9 TB\n",
       "11     2021-2022      243340   246553603363134  246.6 TB\n",
       "12     2022-2023      195372   194356029980378  194.4 TB\n",
       "Total                1786440  1378806653718072    1.4 PB"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Download the data from this table here: <a href='totals_by_fy.csv' target='_blank'>totals_by_fy.csv</a><br>"
      ],
      "text/plain": [
       "/home/anj/ukwa-notebook-apps/totals_by_fy.csv"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "by_fy = dfu.groupby([pd.Grouper(key='timestamp_dt', freq=\"A-MAR\")]).agg(count=('file_size_l', 'count'), size=('file_size_l', 'sum'))\n",
    "\n",
    "# Removed heirarchical index so we can plot:\n",
    "by_fy = by_fy.reset_index()\n",
    "\n",
    "# Transform how FY is presented:\n",
    "by_fy['timestamp_dt'] = by_fy['timestamp_dt'].dt.year.apply(lambda x: str(x-1) + \"-\" + str(x))\n",
    "\n",
    "# Show table and downloader:\n",
    "show_table_and_dl(by_fy, 'totals_by_fy')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Totals by Financial Year, Collection, Stream, Store & Kind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>collection</th>\n",
       "      <th>stream</th>\n",
       "      <th>store</th>\n",
       "      <th>kind</th>\n",
       "      <th>file_count</th>\n",
       "      <th>size_bytes</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-2011</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>21427</td>\n",
       "      <td>51254365367</td>\n",
       "      <td>51.3 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-2011</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>91777</td>\n",
       "      <td>7765638602403</td>\n",
       "      <td>7.8 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011-2012</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>11920</td>\n",
       "      <td>24930586396</td>\n",
       "      <td>24.9 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011-2012</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>48040</td>\n",
       "      <td>4005975723154</td>\n",
       "      <td>4.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012-2013</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>14525</td>\n",
       "      <td>38703889530</td>\n",
       "      <td>38.7 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2012-2013</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>64631</td>\n",
       "      <td>6683085391715</td>\n",
       "      <td>6.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2013-2014</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>9</td>\n",
       "      <td>497880630017</td>\n",
       "      <td>497.9 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2013-2014</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>10</td>\n",
       "      <td>4378472582</td>\n",
       "      <td>4.4 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2013-2014</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>33102</td>\n",
       "      <td>33902836541889</td>\n",
       "      <td>33.9 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2013-2014</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>23</td>\n",
       "      <td>119909960</td>\n",
       "      <td>119.9 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2013-2014</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>10274</td>\n",
       "      <td>7570918166481</td>\n",
       "      <td>7.6 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2013-2014</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>5334</td>\n",
       "      <td>22058302587</td>\n",
       "      <td>22.1 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2013-2014</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>32299</td>\n",
       "      <td>2991217002315</td>\n",
       "      <td>3.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2014-2015</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>228</td>\n",
       "      <td>4882231936</td>\n",
       "      <td>4.9 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2014-2015</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>61196</td>\n",
       "      <td>62133135017950</td>\n",
       "      <td>62.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2014-2015</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>9</td>\n",
       "      <td>27638526</td>\n",
       "      <td>27.6 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2014-2015</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>18112</td>\n",
       "      <td>10139501585284</td>\n",
       "      <td>10.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2014-2015</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>6343</td>\n",
       "      <td>15291860247</td>\n",
       "      <td>15.3 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2014-2015</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>28738</td>\n",
       "      <td>2896978468470</td>\n",
       "      <td>2.9 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2015-2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>109</td>\n",
       "      <td>235613102166</td>\n",
       "      <td>235.6 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2015-2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>199</td>\n",
       "      <td>4570058043</td>\n",
       "      <td>4.6 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2015-2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>74237</td>\n",
       "      <td>75488235762146</td>\n",
       "      <td>75.5 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2015-2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>48</td>\n",
       "      <td>296844607</td>\n",
       "      <td>296.8 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2015-2016</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>20730</td>\n",
       "      <td>19821301955859</td>\n",
       "      <td>19.8 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2015-2016</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>6969</td>\n",
       "      <td>13227273721</td>\n",
       "      <td>13.2 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2015-2016</td>\n",
       "      <td>selective</td>\n",
       "      <td>selective</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>27233</td>\n",
       "      <td>2073194685633</td>\n",
       "      <td>2.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2016-2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>602</td>\n",
       "      <td>1072817352371</td>\n",
       "      <td>1.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2016-2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>246</td>\n",
       "      <td>8708472655</td>\n",
       "      <td>8.7 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2016-2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>102141</td>\n",
       "      <td>103798783257500</td>\n",
       "      <td>103.8 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2016-2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>11569</td>\n",
       "      <td>554374729989</td>\n",
       "      <td>554.4 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2016-2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>149</td>\n",
       "      <td>2246731492</td>\n",
       "      <td>2.2 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2016-2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>29701</td>\n",
       "      <td>26887025236092</td>\n",
       "      <td>26.9 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2016-2017</td>\n",
       "      <td>npld</td>\n",
       "      <td>webrecorder</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>6</td>\n",
       "      <td>491399057</td>\n",
       "      <td>491.4 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2017-2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>239</td>\n",
       "      <td>776208000016</td>\n",
       "      <td>776.2 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2017-2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>145</td>\n",
       "      <td>3748581332</td>\n",
       "      <td>3.7 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2017-2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>76079</td>\n",
       "      <td>76973045845589</td>\n",
       "      <td>77.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2017-2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>7844</td>\n",
       "      <td>538853162961</td>\n",
       "      <td>538.9 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2017-2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>338</td>\n",
       "      <td>4803661</td>\n",
       "      <td>4.8 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2017-2018</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>37354</td>\n",
       "      <td>22432713791284</td>\n",
       "      <td>22.4 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2018-2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>2134</td>\n",
       "      <td>1417051477421</td>\n",
       "      <td>1.4 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2018-2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>445</td>\n",
       "      <td>2075196719</td>\n",
       "      <td>2.1 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2018-2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>59420</td>\n",
       "      <td>57584278800929</td>\n",
       "      <td>57.6 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2018-2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>5343</td>\n",
       "      <td>1504501669239</td>\n",
       "      <td>1.5 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2018-2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>1018</td>\n",
       "      <td>294763988</td>\n",
       "      <td>294.8 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2018-2019</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>84886</td>\n",
       "      <td>75297459907880</td>\n",
       "      <td>75.3 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2019-2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>435</td>\n",
       "      <td>1026758576428</td>\n",
       "      <td>1.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2019-2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>143</td>\n",
       "      <td>1793433956</td>\n",
       "      <td>1.8 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2019-2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>70727</td>\n",
       "      <td>62704803095201</td>\n",
       "      <td>62.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2019-2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>4538</td>\n",
       "      <td>3417576393214</td>\n",
       "      <td>3.4 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2019-2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>838</td>\n",
       "      <td>223817144</td>\n",
       "      <td>223.8 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2019-2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>101776</td>\n",
       "      <td>95616352559320</td>\n",
       "      <td>95.6 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2019-2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>20</td>\n",
       "      <td>14177092595</td>\n",
       "      <td>14.2 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2019-2020</td>\n",
       "      <td>npld</td>\n",
       "      <td>webrecorder</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>98</td>\n",
       "      <td>2791702436</td>\n",
       "      <td>2.8 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2020-2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>133</td>\n",
       "      <td>1098733640099</td>\n",
       "      <td>1.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2020-2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>viral</td>\n",
       "      <td>109</td>\n",
       "      <td>1915066717</td>\n",
       "      <td>1.9 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2020-2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>97540</td>\n",
       "      <td>94105431547498</td>\n",
       "      <td>94.1 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>2020-2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>5</td>\n",
       "      <td>66423142082</td>\n",
       "      <td>66.4 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2020-2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>701</td>\n",
       "      <td>2407680102969</td>\n",
       "      <td>2.4 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2020-2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>101</td>\n",
       "      <td>45998891</td>\n",
       "      <td>46.0 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2020-2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>73382</td>\n",
       "      <td>72192292950993</td>\n",
       "      <td>72.2 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2020-2021</td>\n",
       "      <td>npld</td>\n",
       "      <td>webrecorder</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>1</td>\n",
       "      <td>84005858</td>\n",
       "      <td>84.0 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2021-2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>59</td>\n",
       "      <td>91606900484</td>\n",
       "      <td>91.6 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2021-2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>viral</td>\n",
       "      <td>93</td>\n",
       "      <td>1821844584</td>\n",
       "      <td>1.8 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2021-2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>76094</td>\n",
       "      <td>75658374600860</td>\n",
       "      <td>75.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2021-2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>394</td>\n",
       "      <td>1991080530489</td>\n",
       "      <td>2.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2021-2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>viral</td>\n",
       "      <td>59</td>\n",
       "      <td>129088755</td>\n",
       "      <td>129.1 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2021-2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>warcs</td>\n",
       "      <td>118581</td>\n",
       "      <td>119800045713471</td>\n",
       "      <td>119.8 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2021-2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>102</td>\n",
       "      <td>621760449962</td>\n",
       "      <td>621.8 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2021-2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>viral</td>\n",
       "      <td>36</td>\n",
       "      <td>15880996</td>\n",
       "      <td>15.9 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2021-2022</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>47922</td>\n",
       "      <td>48388768353533</td>\n",
       "      <td>48.4 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2022-2023</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>25</td>\n",
       "      <td>7911759289</td>\n",
       "      <td>7.9 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2022-2023</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>viral</td>\n",
       "      <td>103</td>\n",
       "      <td>2067356488</td>\n",
       "      <td>2.1 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2022-2023</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>108106</td>\n",
       "      <td>106638546143768</td>\n",
       "      <td>106.6 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>2022-2023</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h020</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>299</td>\n",
       "      <td>2659758150753</td>\n",
       "      <td>2.7 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>2022-2023</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>crawl-logs</td>\n",
       "      <td>193</td>\n",
       "      <td>29153265149</td>\n",
       "      <td>29.2 GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>2022-2023</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>viral</td>\n",
       "      <td>68</td>\n",
       "      <td>20118993</td>\n",
       "      <td>20.1 MB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>2022-2023</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>86578</td>\n",
       "      <td>85018573185938</td>\n",
       "      <td>85.0 TB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1786440</td>\n",
       "      <td>1378806653718072</td>\n",
       "      <td>1.4 PB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            year collection       stream   store        kind  file_count  \\\n",
       "0      2010-2011  selective    selective    h020  crawl-logs       21427   \n",
       "1      2010-2011  selective    selective    h020       warcs       91777   \n",
       "2      2011-2012  selective    selective    h020  crawl-logs       11920   \n",
       "3      2011-2012  selective    selective    h020       warcs       48040   \n",
       "4      2012-2013  selective    selective    h020  crawl-logs       14525   \n",
       "5      2012-2013  selective    selective    h020       warcs       64631   \n",
       "6      2013-2014       npld       domain    h020  crawl-logs           9   \n",
       "7      2013-2014       npld       domain    h020       viral          10   \n",
       "8      2013-2014       npld       domain    h020       warcs       33102   \n",
       "9      2013-2014       npld     frequent    h020       viral          23   \n",
       "10     2013-2014       npld     frequent    h020       warcs       10274   \n",
       "11     2013-2014  selective    selective    h020  crawl-logs        5334   \n",
       "12     2013-2014  selective    selective    h020       warcs       32299   \n",
       "13     2014-2015       npld       domain    h020       viral         228   \n",
       "14     2014-2015       npld       domain    h020       warcs       61196   \n",
       "15     2014-2015       npld     frequent    h020       viral           9   \n",
       "16     2014-2015       npld     frequent    h020       warcs       18112   \n",
       "17     2014-2015  selective    selective    h020  crawl-logs        6343   \n",
       "18     2014-2015  selective    selective    h020       warcs       28738   \n",
       "19     2015-2016       npld       domain    h020  crawl-logs         109   \n",
       "20     2015-2016       npld       domain    h020       viral         199   \n",
       "21     2015-2016       npld       domain    h020       warcs       74237   \n",
       "22     2015-2016       npld     frequent    h020       viral          48   \n",
       "23     2015-2016       npld     frequent    h020       warcs       20730   \n",
       "24     2015-2016  selective    selective    h020  crawl-logs        6969   \n",
       "25     2015-2016  selective    selective    h020       warcs       27233   \n",
       "26     2016-2017       npld       domain    h020  crawl-logs         602   \n",
       "27     2016-2017       npld       domain    h020       viral         246   \n",
       "28     2016-2017       npld       domain    h020       warcs      102141   \n",
       "29     2016-2017       npld     frequent    h020  crawl-logs       11569   \n",
       "30     2016-2017       npld     frequent    h020       viral         149   \n",
       "31     2016-2017       npld     frequent    h020       warcs       29701   \n",
       "32     2016-2017       npld  webrecorder    h020       warcs           6   \n",
       "33     2017-2018       npld       domain    h020  crawl-logs         239   \n",
       "34     2017-2018       npld       domain    h020       viral         145   \n",
       "35     2017-2018       npld       domain    h020       warcs       76079   \n",
       "36     2017-2018       npld     frequent    h020  crawl-logs        7844   \n",
       "37     2017-2018       npld     frequent    h020       viral         338   \n",
       "38     2017-2018       npld     frequent    h020       warcs       37354   \n",
       "39     2018-2019       npld       domain    h020  crawl-logs        2134   \n",
       "40     2018-2019       npld       domain    h020       viral         445   \n",
       "41     2018-2019       npld       domain    h020       warcs       59420   \n",
       "42     2018-2019       npld     frequent    h020  crawl-logs        5343   \n",
       "43     2018-2019       npld     frequent    h020       viral        1018   \n",
       "44     2018-2019       npld     frequent    h020       warcs       84886   \n",
       "45     2019-2020       npld       domain    h020  crawl-logs         435   \n",
       "46     2019-2020       npld       domain    h020       viral         143   \n",
       "47     2019-2020       npld       domain    h020       warcs       70727   \n",
       "48     2019-2020       npld     frequent    h020  crawl-logs        4538   \n",
       "49     2019-2020       npld     frequent    h020       viral         838   \n",
       "50     2019-2020       npld     frequent    h020       warcs      101776   \n",
       "51     2019-2020       npld     frequent      h3       warcs          20   \n",
       "52     2019-2020       npld  webrecorder    h020       warcs          98   \n",
       "53     2020-2021       npld       domain  aws_s3  crawl-logs         133   \n",
       "54     2020-2021       npld       domain  aws_s3       viral         109   \n",
       "55     2020-2021       npld       domain  aws_s3       warcs       97540   \n",
       "56     2020-2021       npld       domain    h020  crawl-logs           5   \n",
       "57     2020-2021       npld     frequent    h020  crawl-logs         701   \n",
       "58     2020-2021       npld     frequent    h020       viral         101   \n",
       "59     2020-2021       npld     frequent    h020       warcs       73382   \n",
       "60     2020-2021       npld  webrecorder    h020       warcs           1   \n",
       "61     2021-2022       npld       domain  aws_s3  crawl-logs          59   \n",
       "62     2021-2022       npld       domain  aws_s3       viral          93   \n",
       "63     2021-2022       npld       domain  aws_s3       warcs       76094   \n",
       "64     2021-2022       npld     frequent    h020  crawl-logs         394   \n",
       "65     2021-2022       npld     frequent    h020       viral          59   \n",
       "66     2021-2022       npld     frequent    h020       warcs      118581   \n",
       "67     2021-2022       npld     frequent      h3  crawl-logs         102   \n",
       "68     2021-2022       npld     frequent      h3       viral          36   \n",
       "69     2021-2022       npld     frequent      h3       warcs       47922   \n",
       "70     2022-2023       npld       domain  aws_s3  crawl-logs          25   \n",
       "71     2022-2023       npld       domain  aws_s3       viral         103   \n",
       "72     2022-2023       npld       domain  aws_s3       warcs      108106   \n",
       "73     2022-2023       npld     frequent    h020  crawl-logs         299   \n",
       "74     2022-2023       npld     frequent      h3  crawl-logs         193   \n",
       "75     2022-2023       npld     frequent      h3       viral          68   \n",
       "76     2022-2023       npld     frequent      h3       warcs       86578   \n",
       "Total                                                            1786440   \n",
       "\n",
       "             size_bytes      size  \n",
       "0           51254365367   51.3 GB  \n",
       "1         7765638602403    7.8 TB  \n",
       "2           24930586396   24.9 GB  \n",
       "3         4005975723154    4.0 TB  \n",
       "4           38703889530   38.7 GB  \n",
       "5         6683085391715    6.7 TB  \n",
       "6          497880630017  497.9 GB  \n",
       "7            4378472582    4.4 GB  \n",
       "8        33902836541889   33.9 TB  \n",
       "9             119909960  119.9 MB  \n",
       "10        7570918166481    7.6 TB  \n",
       "11          22058302587   22.1 GB  \n",
       "12        2991217002315    3.0 TB  \n",
       "13           4882231936    4.9 GB  \n",
       "14       62133135017950   62.1 TB  \n",
       "15             27638526   27.6 MB  \n",
       "16       10139501585284   10.1 TB  \n",
       "17          15291860247   15.3 GB  \n",
       "18        2896978468470    2.9 TB  \n",
       "19         235613102166  235.6 GB  \n",
       "20           4570058043    4.6 GB  \n",
       "21       75488235762146   75.5 TB  \n",
       "22            296844607  296.8 MB  \n",
       "23       19821301955859   19.8 TB  \n",
       "24          13227273721   13.2 GB  \n",
       "25        2073194685633    2.1 TB  \n",
       "26        1072817352371    1.1 TB  \n",
       "27           8708472655    8.7 GB  \n",
       "28      103798783257500  103.8 TB  \n",
       "29         554374729989  554.4 GB  \n",
       "30           2246731492    2.2 GB  \n",
       "31       26887025236092   26.9 TB  \n",
       "32            491399057  491.4 MB  \n",
       "33         776208000016  776.2 GB  \n",
       "34           3748581332    3.7 GB  \n",
       "35       76973045845589   77.0 TB  \n",
       "36         538853162961  538.9 GB  \n",
       "37              4803661    4.8 MB  \n",
       "38       22432713791284   22.4 TB  \n",
       "39        1417051477421    1.4 TB  \n",
       "40           2075196719    2.1 GB  \n",
       "41       57584278800929   57.6 TB  \n",
       "42        1504501669239    1.5 TB  \n",
       "43            294763988  294.8 MB  \n",
       "44       75297459907880   75.3 TB  \n",
       "45        1026758576428    1.0 TB  \n",
       "46           1793433956    1.8 GB  \n",
       "47       62704803095201   62.7 TB  \n",
       "48        3417576393214    3.4 TB  \n",
       "49            223817144  223.8 MB  \n",
       "50       95616352559320   95.6 TB  \n",
       "51          14177092595   14.2 GB  \n",
       "52           2791702436    2.8 GB  \n",
       "53        1098733640099    1.1 TB  \n",
       "54           1915066717    1.9 GB  \n",
       "55       94105431547498   94.1 TB  \n",
       "56          66423142082   66.4 GB  \n",
       "57        2407680102969    2.4 TB  \n",
       "58             45998891   46.0 MB  \n",
       "59       72192292950993   72.2 TB  \n",
       "60             84005858   84.0 MB  \n",
       "61          91606900484   91.6 GB  \n",
       "62           1821844584    1.8 GB  \n",
       "63       75658374600860   75.7 TB  \n",
       "64        1991080530489    2.0 TB  \n",
       "65            129088755  129.1 MB  \n",
       "66      119800045713471  119.8 TB  \n",
       "67         621760449962  621.8 GB  \n",
       "68             15880996   15.9 MB  \n",
       "69       48388768353533   48.4 TB  \n",
       "70           7911759289    7.9 GB  \n",
       "71           2067356488    2.1 GB  \n",
       "72      106638546143768  106.6 TB  \n",
       "73        2659758150753    2.7 TB  \n",
       "74          29153265149   29.2 GB  \n",
       "75             20118993   20.1 MB  \n",
       "76       85018573185938   85.0 TB  \n",
       "Total  1378806653718072    1.4 PB  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Download the data from this table here: <a href='totals_by_fy_collection_stream_store_kind.csv' target='_blank'>totals_by_fy_collection_stream_store_kind.csv</a><br>"
      ],
      "text/plain": [
       "/home/anj/ukwa-notebook-apps/totals_by_fy_collection_stream_store_kind.csv"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "by_fy = dfu.groupby([pd.Grouper(key='timestamp_dt', freq=\"A-MAR\"), 'collection_s', 'stream_s', 'hdfs_service_id_s', 'kind_s']).agg(count=('file_size_l', 'count'), size=('file_size_l', 'sum'))\n",
    "\n",
    "# Removed heirarchical index so we can plot:\n",
    "by_fy = by_fy.reset_index()\n",
    "\n",
    "# Transform how FY is presented:\n",
    "by_fy['timestamp_dt'] = by_fy['timestamp_dt'].dt.year.apply(lambda x: str(x-1) + \"-\" + str(x))\n",
    "\n",
    "# Show table and downloader:\n",
    "show_table_and_dl(by_fy, 'totals_by_fy_collection_stream_store_kind')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Graphs of Totals by Stream & Kind, over Time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
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       "      outputDiv = document.getElementById(\"altair-viz-2bfb11170f794b6195a1f8dcf13a4f53\");\n",
       "    }\n",
       "    const paths = {\n",
       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
       "    };\n",
       "\n",
       "    function loadScript(lib) {\n",
       "      return new Promise(function(resolve, reject) {\n",
       "        var s = document.createElement('script');\n",
       "        s.src = paths[lib];\n",
       "        s.async = true;\n",
       "        s.onload = () => resolve(paths[lib]);\n",
       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      });\n",
       "    }\n",
       "\n",
       "    function showError(err) {\n",
       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
       "      throw err;\n",
       "    }\n",
       "\n",
       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else if (typeof vegaEmbed === \"function\") {\n",
       "      displayChart(vegaEmbed);\n",
       "    } else {\n",
       "      loadScript(\"vega\")\n",
       "        .then(() => loadScript(\"vega-lite\"))\n",
       "        .then(() => loadScript(\"vega-embed\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"name\": \"data-dd5c76ea8633a14a752dd9e636863214\"}, \"mark\": \"bar\", \"encoding\": {\"color\": {\"type\": \"nominal\", \"field\": \"stream_s\"}, \"opacity\": {\"condition\": {\"value\": 1, \"selection\": \"selector002\"}, \"value\": 0.2}, \"row\": {\"type\": \"nominal\", \"field\": \"kind_s\", \"title\": \"Kind\"}, \"tooltip\": [{\"type\": \"nominal\", \"field\": \"fy\", \"title\": \"Financial year\"}, {\"type\": \"nominal\", \"field\": \"stream_s\", \"title\": \"Content stream\"}, {\"type\": \"quantitative\", \"field\": \"count\", \"title\": \"Number of files\"}, {\"type\": \"nominal\", \"field\": \"readable_size\", \"title\": \"Total bytes\"}], \"x\": {\"type\": \"nominal\", \"axis\": {\"title\": \"Financial year\"}, \"field\": \"fy\"}, \"y\": {\"type\": \"quantitative\", \"axis\": {\"format\": \"s\", \"title\": \"Total bytes\"}, \"field\": \"size\"}}, \"height\": 200, \"resolve\": {\"scale\": {\"y\": \"independent\"}}, \"selection\": {\"selector002\": {\"type\": \"multi\", \"fields\": [\"stream_s\"], \"bind\": \"legend\"}}, \"width\": 800, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\", \"datasets\": {\"data-dd5c76ea8633a14a752dd9e636863214\": [{\"fy\": \"2010-2011\", \"stream_s\": \"selective\", \"kind_s\": \"crawl-logs\", \"count\": 21427, \"size\": 51254365367, \"readable_size\": \"51.3 GB\"}, {\"fy\": \"2010-2011\", \"stream_s\": \"selective\", \"kind_s\": \"warcs\", \"count\": 91777, \"size\": 7765638602403, \"readable_size\": \"7.8 TB\"}, {\"fy\": \"2011-2012\", \"stream_s\": \"selective\", \"kind_s\": \"crawl-logs\", \"count\": 11920, \"size\": 24930586396, \"readable_size\": \"24.9 GB\"}, {\"fy\": \"2011-2012\", \"stream_s\": \"selective\", \"kind_s\": \"warcs\", \"count\": 48040, \"size\": 4005975723154, \"readable_size\": \"4.0 TB\"}, {\"fy\": \"2012-2013\", \"stream_s\": \"selective\", \"kind_s\": \"crawl-logs\", \"count\": 14525, \"size\": 38703889530, \"readable_size\": \"38.7 GB\"}, {\"fy\": \"2012-2013\", \"stream_s\": \"selective\", \"kind_s\": \"warcs\", \"count\": 64631, \"size\": 6683085391715, \"readable_size\": \"6.7 TB\"}, {\"fy\": \"2013-2014\", \"stream_s\": \"domain\", \"kind_s\": \"crawl-logs\", \"count\": 9, \"size\": 497880630017, \"readable_size\": \"497.9 GB\"}, {\"fy\": \"2013-2014\", \"stream_s\": \"domain\", \"kind_s\": \"viral\", \"count\": 10, \"size\": 4378472582, \"readable_size\": \"4.4 GB\"}, {\"fy\": \"2013-2014\", \"stream_s\": \"domain\", \"kind_s\": \"warcs\", \"count\": 33102, \"size\": 33902836541889, \"readable_size\": \"33.9 TB\"}, {\"fy\": \"2013-2014\", \"stream_s\": \"frequent\", \"kind_s\": \"viral\", \"count\": 23, \"size\": 119909960, \"readable_size\": \"119.9 MB\"}, {\"fy\": \"2013-2014\", \"stream_s\": \"frequent\", \"kind_s\": \"warcs\", \"count\": 10274, \"size\": 7570918166481, \"readable_size\": \"7.6 TB\"}, {\"fy\": \"2013-2014\", \"stream_s\": \"selective\", \"kind_s\": \"crawl-logs\", \"count\": 5334, \"size\": 22058302587, \"readable_size\": \"22.1 GB\"}, {\"fy\": \"2013-2014\", \"stream_s\": \"selective\", \"kind_s\": \"warcs\", \"count\": 32299, \"size\": 2991217002315, \"readable_size\": \"3.0 TB\"}, {\"fy\": \"2014-2015\", \"stream_s\": \"domain\", \"kind_s\": \"viral\", \"count\": 228, \"size\": 4882231936, \"readable_size\": \"4.9 GB\"}, {\"fy\": \"2014-2015\", \"stream_s\": \"domain\", \"kind_s\": \"warcs\", \"count\": 61196, \"size\": 62133135017950, \"readable_size\": \"62.1 TB\"}, {\"fy\": \"2014-2015\", \"stream_s\": \"frequent\", \"kind_s\": \"viral\", \"count\": 9, \"size\": 27638526, \"readable_size\": \"27.6 MB\"}, {\"fy\": \"2014-2015\", \"stream_s\": \"frequent\", \"kind_s\": \"warcs\", \"count\": 18112, \"size\": 10139501585284, \"readable_size\": \"10.1 TB\"}, {\"fy\": \"2014-2015\", \"stream_s\": \"selective\", \"kind_s\": \"crawl-logs\", \"count\": 6343, \"size\": 15291860247, \"readable_size\": \"15.3 GB\"}, {\"fy\": \"2014-2015\", \"stream_s\": \"selective\", \"kind_s\": \"warcs\", \"count\": 28738, \"size\": 2896978468470, \"readable_size\": \"2.9 TB\"}, {\"fy\": \"2015-2016\", \"stream_s\": \"domain\", \"kind_s\": \"crawl-logs\", \"count\": 109, \"size\": 235613102166, \"readable_size\": \"235.6 GB\"}, {\"fy\": \"2015-2016\", \"stream_s\": \"domain\", \"kind_s\": \"viral\", \"count\": 199, \"size\": 4570058043, \"readable_size\": \"4.6 GB\"}, {\"fy\": \"2015-2016\", \"stream_s\": \"domain\", \"kind_s\": \"warcs\", \"count\": 74237, \"size\": 75488235762146, \"readable_size\": \"75.5 TB\"}, {\"fy\": \"2015-2016\", \"stream_s\": \"frequent\", \"kind_s\": \"viral\", \"count\": 48, \"size\": 296844607, \"readable_size\": \"296.8 MB\"}, {\"fy\": \"2015-2016\", \"stream_s\": \"frequent\", \"kind_s\": \"warcs\", \"count\": 20730, \"size\": 19821301955859, \"readable_size\": \"19.8 TB\"}, {\"fy\": \"2015-2016\", \"stream_s\": \"selective\", \"kind_s\": \"crawl-logs\", \"count\": 6969, \"size\": 13227273721, \"readable_size\": \"13.2 GB\"}, {\"fy\": \"2015-2016\", \"stream_s\": \"selective\", \"kind_s\": \"warcs\", \"count\": 27233, \"size\": 2073194685633, \"readable_size\": \"2.1 TB\"}, {\"fy\": \"2016-2017\", \"stream_s\": \"domain\", \"kind_s\": \"crawl-logs\", \"count\": 602, \"size\": 1072817352371, \"readable_size\": \"1.1 TB\"}, {\"fy\": \"2016-2017\", \"stream_s\": \"domain\", \"kind_s\": \"viral\", \"count\": 246, \"size\": 8708472655, \"readable_size\": \"8.7 GB\"}, {\"fy\": \"2016-2017\", \"stream_s\": \"domain\", \"kind_s\": \"warcs\", \"count\": 102141, \"size\": 103798783257500, \"readable_size\": \"103.8 TB\"}, {\"fy\": \"2016-2017\", \"stream_s\": \"frequent\", \"kind_s\": \"crawl-logs\", \"count\": 11569, \"size\": 554374729989, \"readable_size\": \"554.4 GB\"}, {\"fy\": \"2016-2017\", \"stream_s\": \"frequent\", \"kind_s\": \"viral\", \"count\": 149, \"size\": 2246731492, \"readable_size\": \"2.2 GB\"}, {\"fy\": \"2016-2017\", \"stream_s\": \"frequent\", \"kind_s\": \"warcs\", \"count\": 29701, \"size\": 26887025236092, \"readable_size\": \"26.9 TB\"}, {\"fy\": \"2016-2017\", \"stream_s\": \"webrecorder\", \"kind_s\": \"warcs\", \"count\": 6, \"size\": 491399057, \"readable_size\": \"491.4 MB\"}, {\"fy\": \"2017-2018\", \"stream_s\": \"domain\", \"kind_s\": \"crawl-logs\", \"count\": 239, \"size\": 776208000016, \"readable_size\": \"776.2 GB\"}, {\"fy\": \"2017-2018\", \"stream_s\": \"domain\", \"kind_s\": \"viral\", \"count\": 145, \"size\": 3748581332, \"readable_size\": \"3.7 GB\"}, {\"fy\": \"2017-2018\", \"stream_s\": \"domain\", \"kind_s\": \"warcs\", \"count\": 76079, \"size\": 76973045845589, \"readable_size\": \"77.0 TB\"}, {\"fy\": \"2017-2018\", \"stream_s\": \"frequent\", \"kind_s\": \"crawl-logs\", \"count\": 7844, \"size\": 538853162961, \"readable_size\": \"538.9 GB\"}, {\"fy\": \"2017-2018\", \"stream_s\": \"frequent\", \"kind_s\": \"viral\", \"count\": 338, \"size\": 4803661, \"readable_size\": \"4.8 MB\"}, {\"fy\": \"2017-2018\", \"stream_s\": \"frequent\", \"kind_s\": \"warcs\", \"count\": 37354, \"size\": 22432713791284, \"readable_size\": \"22.4 TB\"}, {\"fy\": \"2018-2019\", \"stream_s\": \"domain\", \"kind_s\": \"crawl-logs\", \"count\": 2134, \"size\": 1417051477421, \"readable_size\": \"1.4 TB\"}, {\"fy\": \"2018-2019\", \"stream_s\": \"domain\", \"kind_s\": \"viral\", \"count\": 445, \"size\": 2075196719, \"readable_size\": \"2.1 GB\"}, {\"fy\": \"2018-2019\", \"stream_s\": \"domain\", \"kind_s\": \"warcs\", \"count\": 59420, \"size\": 57584278800929, \"readable_size\": \"57.6 TB\"}, {\"fy\": \"2018-2019\", \"stream_s\": \"frequent\", \"kind_s\": \"crawl-logs\", \"count\": 5343, \"size\": 1504501669239, \"readable_size\": \"1.5 TB\"}, {\"fy\": \"2018-2019\", \"stream_s\": \"frequent\", \"kind_s\": \"viral\", \"count\": 1018, \"size\": 294763988, \"readable_size\": \"294.8 MB\"}, {\"fy\": \"2018-2019\", \"stream_s\": \"frequent\", \"kind_s\": \"warcs\", \"count\": 84886, \"size\": 75297459907880, \"readable_size\": \"75.3 TB\"}, {\"fy\": \"2019-2020\", \"stream_s\": \"domain\", \"kind_s\": \"crawl-logs\", \"count\": 435, \"size\": 1026758576428, \"readable_size\": \"1.0 TB\"}, {\"fy\": \"2019-2020\", \"stream_s\": \"domain\", \"kind_s\": \"viral\", \"count\": 143, \"size\": 1793433956, \"readable_size\": \"1.8 GB\"}, {\"fy\": \"2019-2020\", \"stream_s\": \"domain\", \"kind_s\": \"warcs\", \"count\": 70727, \"size\": 62704803095201, \"readable_size\": \"62.7 TB\"}, {\"fy\": \"2019-2020\", \"stream_s\": \"frequent\", \"kind_s\": \"crawl-logs\", \"count\": 4538, \"size\": 3417576393214, \"readable_size\": \"3.4 TB\"}, {\"fy\": \"2019-2020\", \"stream_s\": \"frequent\", \"kind_s\": \"viral\", \"count\": 838, \"size\": 223817144, \"readable_size\": \"223.8 MB\"}, {\"fy\": \"2019-2020\", \"stream_s\": \"frequent\", \"kind_s\": \"warcs\", \"count\": 101796, \"size\": 95630529651915, \"readable_size\": \"95.6 TB\"}, {\"fy\": \"2019-2020\", \"stream_s\": \"webrecorder\", \"kind_s\": \"warcs\", \"count\": 98, \"size\": 2791702436, \"readable_size\": \"2.8 GB\"}, {\"fy\": \"2020-2021\", \"stream_s\": \"domain\", \"kind_s\": \"crawl-logs\", \"count\": 138, \"size\": 1165156782181, \"readable_size\": \"1.2 TB\"}, {\"fy\": \"2020-2021\", \"stream_s\": \"domain\", \"kind_s\": \"viral\", \"count\": 109, \"size\": 1915066717, \"readable_size\": \"1.9 GB\"}, {\"fy\": \"2020-2021\", \"stream_s\": \"domain\", \"kind_s\": \"warcs\", \"count\": 97540, \"size\": 94105431547498, \"readable_size\": \"94.1 TB\"}, {\"fy\": \"2020-2021\", \"stream_s\": \"frequent\", \"kind_s\": \"crawl-logs\", \"count\": 701, \"size\": 2407680102969, \"readable_size\": \"2.4 TB\"}, {\"fy\": \"2020-2021\", \"stream_s\": \"frequent\", \"kind_s\": \"viral\", \"count\": 101, \"size\": 45998891, \"readable_size\": \"46.0 MB\"}, {\"fy\": \"2020-2021\", \"stream_s\": \"frequent\", \"kind_s\": \"warcs\", \"count\": 73382, \"size\": 72192292950993, \"readable_size\": \"72.2 TB\"}, {\"fy\": \"2020-2021\", \"stream_s\": \"webrecorder\", \"kind_s\": \"warcs\", \"count\": 1, \"size\": 84005858, \"readable_size\": \"84.0 MB\"}, {\"fy\": \"2021-2022\", \"stream_s\": \"domain\", \"kind_s\": \"crawl-logs\", \"count\": 59, \"size\": 91606900484, \"readable_size\": \"91.6 GB\"}, {\"fy\": \"2021-2022\", \"stream_s\": \"domain\", \"kind_s\": \"viral\", \"count\": 93, \"size\": 1821844584, \"readable_size\": \"1.8 GB\"}, {\"fy\": \"2021-2022\", \"stream_s\": \"domain\", \"kind_s\": \"warcs\", \"count\": 76094, \"size\": 75658374600860, \"readable_size\": \"75.7 TB\"}, {\"fy\": \"2021-2022\", \"stream_s\": \"frequent\", \"kind_s\": \"crawl-logs\", \"count\": 496, \"size\": 2612840980451, \"readable_size\": \"2.6 TB\"}, {\"fy\": \"2021-2022\", \"stream_s\": \"frequent\", \"kind_s\": \"viral\", \"count\": 95, \"size\": 144969751, \"readable_size\": \"145.0 MB\"}, {\"fy\": \"2021-2022\", \"stream_s\": \"frequent\", \"kind_s\": \"warcs\", \"count\": 166503, \"size\": 168188814067004, \"readable_size\": \"168.2 TB\"}, {\"fy\": \"2022-2023\", \"stream_s\": \"domain\", \"kind_s\": \"crawl-logs\", \"count\": 25, \"size\": 7911759289, \"readable_size\": \"7.9 GB\"}, {\"fy\": \"2022-2023\", \"stream_s\": \"domain\", \"kind_s\": \"viral\", \"count\": 103, \"size\": 2067356488, \"readable_size\": \"2.1 GB\"}, {\"fy\": \"2022-2023\", \"stream_s\": \"domain\", \"kind_s\": \"warcs\", \"count\": 108106, \"size\": 106638546143768, \"readable_size\": \"106.6 TB\"}, {\"fy\": \"2022-2023\", \"stream_s\": \"frequent\", \"kind_s\": \"crawl-logs\", \"count\": 492, \"size\": 2688911415902, \"readable_size\": \"2.7 TB\"}, {\"fy\": \"2022-2023\", \"stream_s\": \"frequent\", \"kind_s\": \"viral\", \"count\": 68, \"size\": 20118993, \"readable_size\": \"20.1 MB\"}, {\"fy\": \"2022-2023\", \"stream_s\": \"frequent\", \"kind_s\": \"warcs\", \"count\": 86578, \"size\": 85018573185938, \"readable_size\": \"85.0 TB\"}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.Chart(...)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import altair as alt\n",
    "\n",
    "by_fy_s = dfu.groupby([pd.Grouper(key='timestamp_dt', freq=\"A-MAR\"), 'stream_s', 'kind_s']).agg(count=('file_size_l', 'count'), size=('file_size_l', 'sum'))\n",
    "\n",
    "# Removed heirarchical index so we can plot:\n",
    "by_fy_s = by_fy_s.reset_index()\n",
    "\n",
    "# Transform how FY is presented:\n",
    "by_fy_s['fy'] = by_fy_s['timestamp_dt'].dt.year.apply(lambda x: str(x-1) + \"-\" + str(x))\n",
    "\n",
    "# Refactor/renaming:\n",
    "by_fy_s = by_fy_s.filter(['fy', 'stream_s', 'kind_s', 'count', 'size'])\n",
    "\n",
    "# Present sizes in a readable way\n",
    "by_fy_s['readable_size'] = by_fy_s['size'].apply(lambda x: HumanBytes.format(x, True))\n",
    "\n",
    "# Set up the chart:\n",
    "selection = alt.selection_multi(fields=['stream_s'], bind='legend')\n",
    "\n",
    "alt.Chart(by_fy_s).mark_bar().encode(\n",
    "    x=alt.X('fy', axis = alt.Axis(title = 'Financial year')),\n",
    "    y=alt.Y('size', axis = alt.Axis(title = 'Total bytes', format='s')),\n",
    "    color='stream_s',\n",
    "    row=alt.Row('kind_s', title='Kind'),\n",
    "    opacity=alt.condition(selection, alt.value(1), alt.value(0.2)),\n",
    "    tooltip=[\n",
    "        alt.Tooltip('fy', title='Financial year'), \n",
    "        alt.Tooltip('stream_s', title='Content stream'), \n",
    "        alt.Tooltip('count', title='Number of files'), \n",
    "        alt.Tooltip('readable_size', title='Total bytes')\n",
    "    ]\n",
    ").properties(\n",
    "    width=800,height=200\n",
    ").add_selection(\n",
    "    selection\n",
    ").resolve_scale(y='independent')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Radial Visualization\n",
    "\n",
    "This is a work in progress and is not working yet.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>collection</th>\n",
       "      <th>stream</th>\n",
       "      <th>store</th>\n",
       "      <th>kind</th>\n",
       "      <th>size_bytes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-01-18 07:23:42.430000+00:00</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>1006968461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-01-18 07:23:42.429000+00:00</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>1006652852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-01-18 06:57:18.490000+00:00</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>1010961406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-01-18 06:25:34.721000+00:00</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>1021385500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-01-18 06:25:34.719000+00:00</td>\n",
       "      <td>npld</td>\n",
       "      <td>frequent</td>\n",
       "      <td>h3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>1013505131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>287827</th>\n",
       "      <td>2022-12-31 21:12:08.979000+00:00</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>660562655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>287828</th>\n",
       "      <td>2022-12-31 21:12:09.008000+00:00</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>678496443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>287829</th>\n",
       "      <td>2022-12-31 21:12:09.010000+00:00</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>619855137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>287830</th>\n",
       "      <td>2022-12-31 21:38:39.901000+00:00</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>305220706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>287831</th>\n",
       "      <td>2022-12-31 21:38:39.902000+00:00</td>\n",
       "      <td>npld</td>\n",
       "      <td>domain</td>\n",
       "      <td>aws_s3</td>\n",
       "      <td>warcs</td>\n",
       "      <td>350105805</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1786441 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   year collection    stream   store   kind  \\\n",
       "0      2022-01-18 07:23:42.430000+00:00       npld  frequent      h3  warcs   \n",
       "1      2022-01-18 07:23:42.429000+00:00       npld  frequent      h3  warcs   \n",
       "2      2022-01-18 06:57:18.490000+00:00       npld  frequent      h3  warcs   \n",
       "3      2022-01-18 06:25:34.721000+00:00       npld  frequent      h3  warcs   \n",
       "4      2022-01-18 06:25:34.719000+00:00       npld  frequent      h3  warcs   \n",
       "...                                 ...        ...       ...     ...    ...   \n",
       "287827 2022-12-31 21:12:08.979000+00:00       npld    domain  aws_s3  warcs   \n",
       "287828 2022-12-31 21:12:09.008000+00:00       npld    domain  aws_s3  warcs   \n",
       "287829 2022-12-31 21:12:09.010000+00:00       npld    domain  aws_s3  warcs   \n",
       "287830 2022-12-31 21:38:39.901000+00:00       npld    domain  aws_s3  warcs   \n",
       "287831 2022-12-31 21:38:39.902000+00:00       npld    domain  aws_s3  warcs   \n",
       "\n",
       "        size_bytes  \n",
       "0       1006968461  \n",
       "1       1006652852  \n",
       "2       1010961406  \n",
       "3       1021385500  \n",
       "4       1013505131  \n",
       "...            ...  \n",
       "287827   660562655  \n",
       "287828   678496443  \n",
       "287829   619855137  \n",
       "287830   305220706  \n",
       "287831   350105805  \n",
       "\n",
       "[1786441 rows x 6 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "#for gn, g in dfu.groupby([pd.Grouper(key='timestamp_dt', freq=\"A\"), 'collection_s', 'stream_s', 'hdfs_service_id_s', 'kind_s']):\n",
    "dfuu = dfu.filter(['timestamp_dt', 'collection_s', 'stream_s', 'hdfs_service_id_s', 'kind_s', 'file_size_l']).rename(\n",
    "    columns={\n",
    "        'file_size_l': 'size_bytes', \n",
    "        'kind_s': 'kind', \n",
    "        'stream_s': 'stream',\n",
    "        'count': 'file_count',\n",
    "        'timestamp_dt': 'year',\n",
    "        'collection_s': 'collection',\n",
    "        'hdfs_service_id_s': 'store'\n",
    "    }\n",
    ")\n",
    "dfuu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2010\n",
      "2010 selective 5128 889707367400\n",
      "2010 selective selective\n",
      "2010 selective selective crawl-logs\n",
      "2010 selective selective crawl-logs h020 50 16174178\n",
      "2010 selective selective warcs\n",
      "2010 selective selective warcs h020 5078 889691193222\n",
      "2011\n",
      "2011 selective 152823 9752750101708\n",
      "2011 selective selective\n",
      "2011 selective selective crawl-logs\n",
      "2011 selective selective crawl-logs h020 30896 70177720850\n",
      "2011 selective selective warcs\n",
      "2011 selective selective warcs h020 121927 9682572380858\n",
      "2012\n",
      "2012 selective 62693 5155656912300\n",
      "2012 selective selective\n",
      "2012 selective selective crawl-logs\n",
      "2012 selective selective crawl-logs h020 11337 29180359746\n",
      "2012 selective selective warcs\n",
      "2012 selective selective warcs h020 51356 5126476552554\n",
      "2013\n",
      "2013 npld 39719 39651261733311\n",
      "2013 npld domain\n",
      "2013 npld domain crawl-logs\n",
      "2013 npld domain crawl-logs h020 9 497880630017\n",
      "2013 npld domain viral\n",
      "2013 npld domain viral h020 10 4378472582\n",
      "2013 npld domain warcs\n",
      "2013 npld domain warcs h020 33102 33902836541889\n",
      "2013 npld frequent\n",
      "2013 npld frequent viral\n",
      "2013 npld frequent viral h020 17 99041071\n",
      "2013 npld frequent warcs\n",
      "2013 npld frequent warcs h020 6581 5246067047752\n",
      "2013 selective 59847 4975222824213\n",
      "2013 selective selective\n",
      "2013 selective selective crawl-logs\n",
      "2013 selective selective crawl-logs h020 9853 30828782244\n",
      "2013 selective selective warcs\n",
      "2013 selective selective warcs h020 49994 4944394041969\n",
      "2014\n",
      "2014 npld 77222 71825678300361\n",
      "2014 npld domain\n",
      "2014 npld domain viral\n",
      "2014 npld domain viral h020 228 4882231936\n",
      "2014 npld domain warcs\n",
      "2014 npld domain warcs h020 61196 62133135017950\n",
      "2014 npld frequent\n",
      "2014 npld frequent viral\n",
      "2014 npld frequent viral h020 11 34269049\n",
      "2014 npld frequent warcs\n",
      "2014 npld frequent warcs h020 15787 9687626781426\n",
      "2014 selective 34123 3139804697776\n",
      "2014 selective selective\n",
      "2014 selective selective crawl-logs\n",
      "2014 selective selective crawl-logs h020 5065 17389874737\n",
      "2014 selective selective warcs\n",
      "2014 selective selective warcs h020 29058 3122414823039\n",
      "2015\n",
      "2015 npld 93216 90102310863233\n",
      "2015 npld domain\n",
      "2015 npld domain crawl-logs\n",
      "2015 npld domain crawl-logs h020 109 235613102166\n",
      "2015 npld domain viral\n",
      "2015 npld domain viral h020 199 4570058043\n",
      "2015 npld domain warcs\n",
      "2015 npld domain warcs h020 74237 75488235762146\n",
      "2015 npld frequent\n",
      "2015 npld frequent viral\n",
      "2015 npld frequent viral h020 36 271945467\n",
      "2015 npld frequent warcs\n",
      "2015 npld frequent warcs h020 18635 14373619995411\n",
      "2015 selective 38026 2274712770332\n",
      "2015 selective selective\n",
      "2015 selective selective crawl-logs\n",
      "2015 selective selective crawl-logs h020 7945 15662303216\n",
      "2015 selective selective warcs\n",
      "2015 selective selective warcs h020 30081 2259050467116\n",
      "2016\n",
      "2016 npld 130400 131562200904391\n",
      "2016 npld domain\n",
      "2016 npld domain crawl-logs\n",
      "2016 npld domain crawl-logs h020 587 1021393765281\n",
      "2016 npld domain viral\n",
      "2016 npld domain viral h020 237 8012152161\n",
      "2016 npld domain warcs\n",
      "2016 npld domain warcs h020 102141 103798783257500\n",
      "2016 npld frequent\n",
      "2016 npld frequent crawl-logs\n",
      "2016 npld frequent crawl-logs h020 92 40202387198\n",
      "2016 npld frequent viral\n",
      "2016 npld frequent viral h020 125 2170071165\n",
      "2016 npld frequent warcs\n",
      "2016 npld frequent warcs h020 27212 26691147872029\n",
      "2016 npld webrecorder\n",
      "2016 npld webrecorder warcs\n",
      "2016 npld webrecorder warcs h020 6 491399057\n",
      "2016 selective 6596 393701477809\n",
      "2016 selective selective\n",
      "2016 selective selective crawl-logs\n",
      "2016 selective selective crawl-logs h020 1372 2211062877\n",
      "2016 selective selective warcs\n",
      "2016 selective selective warcs h020 5224 391490414932\n",
      "2017\n",
      "2017 npld 135265 104515586779827\n",
      "2017 npld domain\n",
      "2017 npld domain crawl-logs\n",
      "2017 npld domain crawl-logs h020 254 827631587106\n",
      "2017 npld domain viral\n",
      "2017 npld domain viral h020 154 4444901826\n",
      "2017 npld domain warcs\n",
      "2017 npld domain warcs h020 76079 76973045845589\n",
      "2017 npld frequent\n",
      "2017 npld frequent crawl-logs\n",
      "2017 npld frequent crawl-logs h020 18035 933573121920\n",
      "2017 npld frequent viral\n",
      "2017 npld frequent viral h020 346 119883019\n",
      "2017 npld frequent warcs\n",
      "2017 npld frequent warcs h020 40397 25776771440367\n",
      "2018\n",
      "2018 npld 139734 120955715797493\n",
      "2018 npld domain\n",
      "2018 npld domain crawl-logs\n",
      "2018 npld domain crawl-logs h020 2109 1417051338354\n",
      "2018 npld domain viral\n",
      "2018 npld domain viral h020 445 2075196719\n",
      "2018 npld domain warcs\n",
      "2018 npld domain warcs h020 59420 57584278800929\n",
      "2018 npld frequent\n",
      "2018 npld frequent crawl-logs\n",
      "2018 npld frequent crawl-logs h020 5768 1273256843460\n",
      "2018 npld frequent viral\n",
      "2018 npld frequent viral h020 707 255134402\n",
      "2018 npld frequent warcs\n",
      "2018 npld frequent warcs h020 71285 60678798483629\n",
      "2019\n",
      "2019 npld 187203 169359134779426\n",
      "2019 npld domain\n",
      "2019 npld domain crawl-logs\n",
      "2019 npld domain crawl-logs h020 451 998109935920\n",
      "2019 npld domain viral\n",
      "2019 npld domain viral h020 139 1771940785\n",
      "2019 npld domain warcs\n",
      "2019 npld domain warcs h020 70727 62704803095201\n",
      "2019 npld frequent\n",
      "2019 npld frequent crawl-logs\n",
      "2019 npld frequent crawl-logs h020 4924 3306036343595\n",
      "2019 npld frequent viral\n",
      "2019 npld frequent viral h020 1152 244227036\n",
      "2019 npld frequent warcs\n",
      "2019 npld frequent warcs h020 109693 102332853678911\n",
      "2019 npld frequent warcs h3 20 14177092595\n",
      "2019 npld webrecorder\n",
      "2019 npld webrecorder warcs\n",
      "2019 npld webrecorder warcs h020 97 1138465383\n",
      "2020\n",
      "2020 npld 157614 154867303109935\n",
      "2020 npld domain\n",
      "2020 npld domain crawl-logs\n",
      "2020 npld domain crawl-logs aws_s3 122 1067608520089\n",
      "2020 npld domain crawl-logs h020 14 95071921657\n",
      "2020 npld domain viral\n",
      "2020 npld domain viral aws_s3 105 1914939285\n",
      "2020 npld domain viral h020 4 21493171\n",
      "2020 npld domain warcs\n",
      "2020 npld domain warcs aws_s3 97540 94105431547498\n",
      "2020 npld frequent\n",
      "2020 npld frequent crawl-logs\n",
      "2020 npld frequent crawl-logs h020 1020 2352251432914\n",
      "2020 npld frequent viral\n",
      "2020 npld frequent viral h020 105 64387232\n",
      "2020 npld frequent warcs\n",
      "2020 npld frequent warcs h020 58703 57243285631036\n",
      "2020 npld webrecorder\n",
      "2020 npld webrecorder warcs\n",
      "2020 npld webrecorder warcs h020 1 1653237053\n",
      "2021\n",
      "2021 npld 234377 236937217445920\n",
      "2021 npld domain\n",
      "2021 npld domain crawl-logs\n",
      "2021 npld domain crawl-logs aws_s3 69 111488149755\n",
      "2021 npld domain viral\n",
      "2021 npld domain viral aws_s3 96 1821826003\n",
      "2021 npld domain warcs\n",
      "2021 npld domain warcs aws_s3 76094 75658374600860\n",
      "2021 npld frequent\n",
      "2021 npld frequent crawl-logs\n",
      "2021 npld frequent crawl-logs h020 519 2249613390697\n",
      "2021 npld frequent crawl-logs h3 11 113465607726\n",
      "2021 npld frequent viral\n",
      "2021 npld frequent viral h020 84 130638583\n",
      "2021 npld frequent viral h3 2 1786801\n",
      "2021 npld frequent warcs\n",
      "2021 npld frequent warcs h020 146503 147727440936103\n",
      "2021 npld frequent warcs h3 10998 11074796503534\n",
      "2021 npld webrecorder\n",
      "2021 npld webrecorder warcs\n",
      "2021 npld webrecorder warcs h020 1 84005858\n",
      "2022\n",
      "2022 npld 225159 225102995109197\n",
      "2022 npld domain\n",
      "2022 npld domain crawl-logs\n",
      "2022 npld domain crawl-logs aws_s3 26 19155630028\n",
      "2022 npld domain viral\n",
      "2022 npld domain viral aws_s3 104 2067502501\n",
      "2022 npld domain warcs\n",
      "2022 npld domain warcs aws_s3 108106 106638546143768\n",
      "2022 npld frequent\n",
      "2022 npld frequent crawl-logs\n",
      "2022 npld frequent crawl-logs h020 305 2740058175535\n",
      "2022 npld frequent crawl-logs h3 260 537439199771\n",
      "2022 npld frequent viral\n",
      "2022 npld frequent viral h3 94 33918738\n",
      "2022 npld frequent warcs\n",
      "2022 npld frequent warcs h3 116264 115165694538856\n",
      "2023\n",
      "2023 npld 7295 7345692743440\n",
      "2023 npld frequent\n",
      "2023 npld frequent crawl-logs\n",
      "2023 npld frequent crawl-logs h020 25 178833044295\n",
      "2023 npld frequent crawl-logs h3 24 8907614\n",
      "2023 npld frequent viral\n",
      "2023 npld frequent viral h3 8 294450\n",
      "2023 npld frequent warcs\n",
      "2023 npld frequent warcs h3 7238 7166850497081\n"
     ]
    }
   ],
   "source": [
    "# Build up items for the tree:\n",
    "#  {\n",
    "#    \"id\": 246,\n",
    "#    \"name\": \"TreeMapLayout\",\n",
    "#    \"parent\": 231,\n",
    "#    \"size\": 9191\n",
    "#  },\n",
    "\n",
    "\n",
    "entries = []\n",
    "entry_id = 0\n",
    "\n",
    "entries.append({\n",
    "    'id': entry_id,\n",
    "    'name': \"total\",\n",
    "    'size': dfuu['size_bytes'].sum(),\n",
    "    'count': dfuu['size_bytes'].count()\n",
    "})\n",
    "parent_id = entry_id\n",
    "entry_id += 1\n",
    "\n",
    "for ts, ts_g in dfuu.groupby(pd.Grouper(key='year', freq=\"A\")):\n",
    "    print(ts.year)\n",
    "    for col, col_g in ts_g.groupby('collection'):\n",
    "        print(ts.year, col, col_g['size_bytes'].count(), col_g['size_bytes'].sum())\n",
    "        for stream, stream_g in col_g.groupby('stream'):\n",
    "            print(ts.year, col, stream)\n",
    "            for kind, kind_g in stream_g.groupby('kind'):\n",
    "                print(ts.year, col, stream, kind)\n",
    "                for store, store_g in kind_g.groupby('store'):\n",
    "                    print(ts.year, col, stream, kind, store, store_g['size_bytes'].count(), store_g['size_bytes'].sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.vega.v5+json": {
       "$schema": "https://vega.github.io/schema/vega/v5.json",
       "autosize": "none",
       "data": [
        {
         "name": "tree",
         "transform": [
          {
           "key": "id",
           "parentKey": "parent",
           "type": "stratify"
          },
          {
           "as": [
            "a0",
            "r0",
            "a1",
            "r1",
            "depth",
            "children"
           ],
           "field": "size",
           "size": [
            {
             "signal": "2 * PI"
            },
            {
             "signal": "width / 2"
            }
           ],
           "sort": {
            "field": "value"
           },
           "type": "partition"
          }
         ],
         "url": "https://vega.github.io/vega/data/flare.json"
        }
       ],
       "description": "An example of a space-fulling radial layout for hierarchical data.",
       "height": 600,
       "marks": [
        {
         "encode": {
          "enter": {
           "fill": {
            "field": "depth",
            "scale": "color"
           },
           "tooltip": {
            "signal": "datum.name + (datum.size ? ', ' + datum.size + ' bytes' : '')"
           },
           "x": {
            "signal": "width / 2"
           },
           "y": {
            "signal": "height / 2"
           }
          },
          "hover": {
           "stroke": {
            "value": "red"
           },
           "strokeWidth": {
            "value": 1.5
           },
           "zindex": {
            "value": 1
           }
          },
          "update": {
           "endAngle": {
            "field": "a1"
           },
           "innerRadius": {
            "field": "r0"
           },
           "outerRadius": {
            "field": "r1"
           },
           "startAngle": {
            "field": "a0"
           },
           "stroke": {
            "value": "white"
           },
           "strokeWidth": {
            "value": 0.75
           },
           "zindex": {
            "value": 0
           }
          }
         },
         "from": {
          "data": "tree"
         },
         "type": "arc"
        }
       ],
       "padding": 5,
       "scales": [
        {
         "domain": {
          "data": "tree",
          "field": "depth"
         },
         "name": "color",
         "range": {
          "scheme": "tableau10"
         },
         "type": "ordinal"
        }
       ],
       "width": 600
      },
      "image/png": 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",
      "text/plain": [
       "<Vega 5 object>\n",
       "\n",
       "If you see this message, it means the renderer has not been properly enabled\n",
       "for the frontend that you are using. For more information, see\n",
       "https://altair-viz.github.io/user_guide/troubleshooting.html\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from altair.vega import vega\n",
    "\n",
    "vega({\n",
    "  \"$schema\": \"https://vega.github.io/schema/vega/v5.json\",\n",
    "  \"description\": \"An example of a space-fulling radial layout for hierarchical data.\",\n",
    "  \"width\": 600,\n",
    "  \"height\": 600,\n",
    "  \"padding\": 5,\n",
    "  \"autosize\": \"none\",\n",
    "\n",
    "  \"data\": [\n",
    "    {\n",
    "      \"name\": \"tree\",\n",
    "      \"url\": \"https://vega.github.io/vega/data/flare.json\",\n",
    "      \"transform\": [\n",
    "        {\n",
    "          \"type\": \"stratify\",\n",
    "          \"key\": \"id\",\n",
    "          \"parentKey\": \"parent\"\n",
    "        },\n",
    "        {\n",
    "          \"type\": \"partition\",\n",
    "          \"field\": \"size\",\n",
    "          \"sort\": {\"field\": \"value\"},\n",
    "          \"size\": [{\"signal\": \"2 * PI\"}, {\"signal\": \"width / 2\"}],\n",
    "          \"as\": [\"a0\", \"r0\", \"a1\", \"r1\", \"depth\", \"children\"]\n",
    "        }\n",
    "      ]\n",
    "    }\n",
    "  ],\n",
    "\n",
    "  \"scales\": [\n",
    "    {\n",
    "      \"name\": \"color\",\n",
    "      \"type\": \"ordinal\",\n",
    "      \"domain\": {\"data\": \"tree\", \"field\": \"depth\"},\n",
    "      \"range\": {\"scheme\": \"tableau10\"}\n",
    "    }\n",
    "  ],\n",
    "\n",
    "  \"marks\": [\n",
    "    {\n",
    "      \"type\": \"arc\",\n",
    "      \"from\": {\"data\": \"tree\"},\n",
    "      \"encode\": {\n",
    "        \"enter\": {\n",
    "          \"x\": {\"signal\": \"width / 2\"},\n",
    "          \"y\": {\"signal\": \"height / 2\"},\n",
    "          \"fill\": {\"scale\": \"color\", \"field\": \"depth\"},\n",
    "          \"tooltip\": {\"signal\": \"datum.name + (datum.size ? ', ' + datum.size + ' bytes' : '')\"}\n",
    "        },\n",
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