2_3. EDA- User In-State and Out-of-State Behavior Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "50aa1ccd",
   "metadata": {},
   "source": [
    "# User In-State and Out-of-State Behavior Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96af9046",
   "metadata": {},
   "source": [
    "### Setting up enviroment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9b722be4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Python Stuff\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "from math import sin, cos, sqrt, atan2, radians\n",
    "\n",
    "# PySpark Stuff \n",
    "from pyspark.sql.functions import col, desc, avg\n",
    "from pyspark.sql import functions as F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4fa3fc34",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_rows', None)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "facd6a7b",
   "metadata": {},
   "source": [
    "### Loading Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e5403abf",
   "metadata": {},
   "outputs": [],
   "source": [
    "table_b = 'red-formula-339716:gfds.yelp_business_basicdata'\n",
    "df_b = spark.read.format('bigquery').option('table', table_b).load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ef3eaf74",
   "metadata": {},
   "outputs": [],
   "source": [
    "table_re = 'red-formula-339716:gfds.yelp_review'\n",
    "df_re = spark.read.format('bigquery').option('table', table_re).load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "98186c99",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_review_slim = df_re.select(['user_id', 'business_id'])\n",
    "df_business_slim = df_b.select(['business_id', 'city', 'state'])\n",
    "df_review_business = df_review_slim.join(df_business_slim, on = 'business_id', how = 'inner').dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c2e174c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+--------------------+---------+-----+\n",
      "|         business_id|             user_id|     city|state|\n",
      "+--------------------+--------------------+---------+-----+\n",
      "|y-vHCBFQCDMwzsMwJ...|6iyM-H6_bI13gl4Zn...| Portland|   OR|\n",
      "|P0Ltl7wZFDlHofnPq...|FVk12H4Cz4DkRzl8N...|Beaverton|   OR|\n",
      "+--------------------+--------------------+---------+-----+\n",
      "only showing top 2 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df_review_business.show(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "130a19d3",
   "metadata": {},
   "source": [
    "### Figuring out where the users are"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "00df5f7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Give user a home state based on the state they most reviewed in. \n",
    "# If a person made half of all reviews in the same state, consider him/her living in the state.\n",
    "\n",
    "# Count review for each state\n",
    "user_state_df = df_review_business.groupby(['user_id', 'state']).count().withColumnRenamed(\"count\", \"state_count\")\n",
    "\n",
    "# Count total review \n",
    "user_df = df_review_business.groupby(['user_id']).count().withColumnRenamed(\"count\", \"total_count\")\n",
    "\n",
    "# Caluculate each state's percentage\n",
    "user_state_df = user_state_df.join(user_df, on = 'user_id', how = 'left')\n",
    "user_state_df = user_state_df.withColumn('state_percentage', col(\"state_count\") / col(\"total_count\"))\n",
    "\n",
    "Threshold = 0.50001\n",
    "user_state_df = user_state_df.withColumn('local', F.when((col(\"state_percentage\") > Threshold), 1).otherwise(0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "de64b24f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 10:>                                                         (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+-----+-----------+-----------+------------------+-----+\n",
      "|             user_id|state|state_count|total_count|  state_percentage|local|\n",
      "+--------------------+-----+-----------+-----------+------------------+-----+\n",
      "|--0666UC6t7DJWO4m...|   FL|          1|          1|               1.0|    1|\n",
      "|--0LWpVOR539pgBvl...|   MA|          1|          1|               1.0|    1|\n",
      "|--19CSe_41_fEKvfV...|   CO|          1|          1|               1.0|    1|\n",
      "|--2GHi3yi8D4yBuUY...|   OR|          2|          2|               1.0|    1|\n",
      "|--2JSDM9cMaxm8CHX...|   CO|          1|          1|               1.0|    1|\n",
      "|--56dSK1Y7agEMyIJ...|   TX|          1|          1|               1.0|    1|\n",
      "|--5FEgQNB3_7Wtjxk...|   WA|          4|          6|0.6666666666666666|    1|\n",
      "|--5FEgQNB3_7Wtjxk...|   OR|          2|          6|0.3333333333333333|    0|\n",
      "|--9BvAldSQW8wmAn0...|   OR|          1|          1|               1.0|    1|\n",
      "|--A8rRSzpXtQ0MzgY...|   MA|         10|         10|               1.0|    1|\n",
      "+--------------------+-----+-----------+-----------+------------------+-----+\n",
      "only showing top 10 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "user_state_df.show(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1a827552",
   "metadata": {},
   "outputs": [],
   "source": [
    "user_state_labels = user_state_df.select(['user_id', 'state']).where(user_state_df.local == 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e15b9f3",
   "metadata": {},
   "source": [
    "### Figure out where the reviews came from"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b50d0cf3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# For each review, give user state labels\n",
    "df_re_us = df_re.select('user_id', 'business_id', 'stars').join(user_state_labels, on = 'user_id', how = 'left').withColumnRenamed(\"state\", \"user_state\")\n",
    "df_re_us = df_re_us.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7b90df07",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 21:>                                                         (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+--------------------+-----+----------+\n",
      "|             user_id|         business_id|stars|user_state|\n",
      "+--------------------+--------------------+-----+----------+\n",
      "|--0666UC6t7DJWO4m...|5xS76cdT7THG14H_W...|  1.0|        FL|\n",
      "|--0LWpVOR539pgBvl...|QVnatPo7jCEh9FcKl...|  1.0|        MA|\n",
      "|--19CSe_41_fEKvfV...|i7jMAf1cZJ9h1FRTQ...|  5.0|        CO|\n",
      "+--------------------+--------------------+-----+----------+\n",
      "only showing top 3 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "df_re_us.show(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a1d2a6cc",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 33:>                                                         (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+--------------------+-----+----------+--------------+\n",
      "|         business_id|             user_id|stars|user_state|business_state|\n",
      "+--------------------+--------------------+-----+----------+--------------+\n",
      "|5xS76cdT7THG14H_W...|--0666UC6t7DJWO4m...|  1.0|        FL|            FL|\n",
      "|QVnatPo7jCEh9FcKl...|--0LWpVOR539pgBvl...|  1.0|        MA|            MA|\n",
      "|i7jMAf1cZJ9h1FRTQ...|--19CSe_41_fEKvfV...|  5.0|        CO|            CO|\n",
      "+--------------------+--------------------+-----+----------+--------------+\n",
      "only showing top 3 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "# For each review, give business state labels\n",
    "df_re_lb = df_re_us.join(df_b.select('business_id', 'state'), on = 'business_id', how = 'left').withColumnRenamed(\"state\", \"business_state\")\n",
    "df_re_lb.show(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e01fe4f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# See if review was from in state or out of state\n",
    "df_re_lb = df_re_lb.withColumn('in_state', F.when((col(\"user_state\") == col(\"business_state\")), 1).otherwise(0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e758f93e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 45:>                                                         (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+--------------------+-----+----------+--------------+--------+\n",
      "|         business_id|             user_id|stars|user_state|business_state|in_state|\n",
      "+--------------------+--------------------+-----+----------+--------------+--------+\n",
      "|5xS76cdT7THG14H_W...|--0666UC6t7DJWO4m...|  1.0|        FL|            FL|       1|\n",
      "|QVnatPo7jCEh9FcKl...|--0LWpVOR539pgBvl...|  1.0|        MA|            MA|       1|\n",
      "|i7jMAf1cZJ9h1FRTQ...|--19CSe_41_fEKvfV...|  5.0|        CO|            CO|       1|\n",
      "|lAMX7ndl9sJh117Qh...|--2GHi3yi8D4yBuUY...|  4.0|        OR|            OR|       1|\n",
      "|1jW2Voh5XE7Yt6ZV-...|--2GHi3yi8D4yBuUY...|  5.0|        OR|            OR|       1|\n",
      "|IdY70ew8MHW_1rTvB...|--2JSDM9cMaxm8CHX...|  5.0|        CO|            CO|       1|\n",
      "|ZHxrgZY4NAqtnsBuo...|--56dSK1Y7agEMyIJ...|  4.0|        TX|            TX|       1|\n",
      "|huveiOZFjsFI_Aiq9...|--5FEgQNB3_7Wtjxk...|  4.0|        WA|            WA|       1|\n",
      "|ggqr9BEklylICKl77...|--5FEgQNB3_7Wtjxk...|  2.0|        WA|            WA|       1|\n",
      "|kj77ZrCsFlVuqWkIr...|--5FEgQNB3_7Wtjxk...|  5.0|        WA|            WA|       1|\n",
      "+--------------------+--------------------+-----+----------+--------------+--------+\n",
      "only showing top 10 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "df_re_lb.show(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "45b7623a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 57:================================================>       (13 + 2) / 15]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------+-------+\n",
      "|user_state|  count|\n",
      "+----------+-------+\n",
      "|        MA|2053862|\n",
      "|        TX|1483963|\n",
      "|        OR|1414248|\n",
      "|        GA|1116795|\n",
      "|        FL|1087386|\n",
      "|        BC| 601700|\n",
      "|        OH| 421275|\n",
      "|        CO| 131227|\n",
      "|        WA|  98505|\n",
      "|        CA|    162|\n",
      "+----------+-------+\n",
      "only showing top 10 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "df_re_lb.groupby('user_state').count().orderBy(desc(\"count\")).show(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "90a84245",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Will be looking into the top 7\n",
    "state_list = [\"MA\", \"TX\", \"OR\", \"GA\", \"FL\", \"BC\", \"OH\"]\n",
    "df_re_lb = df_re_lb.where(df_re_lb.user_state.isin(state_list))\n",
    "df_re_lb = df_re_lb.where(df_re_lb.business_state.isin(state_list))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5d65b426",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "df_re_lb_1 = df_re_lb.groupby('user_state').pivot('business_state').count().fillna(0)\n",
    "pd_ubc = df_re_lb_1.select('user_state', \"OR\", \"BC\", \"OH\", \"TX\", \"GA\", \"MA\", \"FL\").toPandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "9b533639",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "df_re_lb_2 = df_re_lb.groupby('user_state').pivot('business_state').agg(avg(\"stars\")).fillna(0)\n",
    "pd_ubs = df_re_lb_2.select('user_state', \"OR\", \"BC\", \"OH\", \"TX\", \"GA\", \"MA\", \"FL\").toPandas()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dea7258e",
   "metadata": {},
   "source": [
    "### Create heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2ee56e82",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create heatmap\n",
    "# Count\n",
    "pd_ubc = pd_ubc.set_index(\"user_state\")\n",
    "np.fill_diagonal(pd_ubc.values, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3b1e357f",
   "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>OR</th>\n",
       "      <th>BC</th>\n",
       "      <th>OH</th>\n",
       "      <th>TX</th>\n",
       "      <th>GA</th>\n",
       "      <th>MA</th>\n",
       "      <th>FL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>OR</th>\n",
       "      <td>0</td>\n",
       "      <td>9141</td>\n",
       "      <td>1243</td>\n",
       "      <td>7767</td>\n",
       "      <td>4582</td>\n",
       "      <td>8517</td>\n",
       "      <td>4776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BC</th>\n",
       "      <td>8449</td>\n",
       "      <td>0</td>\n",
       "      <td>211</td>\n",
       "      <td>1348</td>\n",
       "      <td>862</td>\n",
       "      <td>2281</td>\n",
       "      <td>1609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OH</th>\n",
       "      <td>1195</td>\n",
       "      <td>372</td>\n",
       "      <td>0</td>\n",
       "      <td>1531</td>\n",
       "      <td>2345</td>\n",
       "      <td>2594</td>\n",
       "      <td>3238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TX</th>\n",
       "      <td>8743</td>\n",
       "      <td>2545</td>\n",
       "      <td>1668</td>\n",
       "      <td>0</td>\n",
       "      <td>6990</td>\n",
       "      <td>10070</td>\n",
       "      <td>7540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GA</th>\n",
       "      <td>3943</td>\n",
       "      <td>1552</td>\n",
       "      <td>2063</td>\n",
       "      <td>5687</td>\n",
       "      <td>0</td>\n",
       "      <td>9009</td>\n",
       "      <td>14810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA</th>\n",
       "      <td>9272</td>\n",
       "      <td>3645</td>\n",
       "      <td>2570</td>\n",
       "      <td>10059</td>\n",
       "      <td>10252</td>\n",
       "      <td>0</td>\n",
       "      <td>14486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FL</th>\n",
       "      <td>3819</td>\n",
       "      <td>1874</td>\n",
       "      <td>2229</td>\n",
       "      <td>5727</td>\n",
       "      <td>14152</td>\n",
       "      <td>9535</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              OR    BC    OH     TX     GA     MA     FL\n",
       "user_state                                              \n",
       "OR             0  9141  1243   7767   4582   8517   4776\n",
       "BC          8449     0   211   1348    862   2281   1609\n",
       "OH          1195   372     0   1531   2345   2594   3238\n",
       "TX          8743  2545  1668      0   6990  10070   7540\n",
       "GA          3943  1552  2063   5687      0   9009  14810\n",
       "MA          9272  3645  2570  10059  10252      0  14486\n",
       "FL          3819  1874  2229   5727  14152   9535      0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_ubc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "80ecf1a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set(rc = {'figure.figsize':(15,8)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "27c3dff0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "h = sns.heatmap(pd_ubc, annot=True,fmt=\".1f\", cmap=\"BuPu\")\n",
    "fig = h.get_figure()\n",
    "fig.savefig(\"ubc.png\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "55ed517c",
   "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>OR</th>\n",
       "      <th>BC</th>\n",
       "      <th>OH</th>\n",
       "      <th>TX</th>\n",
       "      <th>GA</th>\n",
       "      <th>MA</th>\n",
       "      <th>FL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>OR</th>\n",
       "      <td>3.866465</td>\n",
       "      <td>3.956460</td>\n",
       "      <td>3.757039</td>\n",
       "      <td>4.001287</td>\n",
       "      <td>3.708206</td>\n",
       "      <td>3.802630</td>\n",
       "      <td>3.692002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BC</th>\n",
       "      <td>4.015150</td>\n",
       "      <td>3.607017</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.968843</td>\n",
       "      <td>3.635731</td>\n",
       "      <td>3.760193</td>\n",
       "      <td>3.731510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OH</th>\n",
       "      <td>4.052720</td>\n",
       "      <td>4.077957</td>\n",
       "      <td>3.688640</td>\n",
       "      <td>3.937296</td>\n",
       "      <td>3.715139</td>\n",
       "      <td>3.833462</td>\n",
       "      <td>3.749846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TX</th>\n",
       "      <td>4.088185</td>\n",
       "      <td>4.008251</td>\n",
       "      <td>3.902278</td>\n",
       "      <td>3.822535</td>\n",
       "      <td>3.736767</td>\n",
       "      <td>3.811718</td>\n",
       "      <td>3.688064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GA</th>\n",
       "      <td>4.078620</td>\n",
       "      <td>3.932990</td>\n",
       "      <td>3.708677</td>\n",
       "      <td>3.979075</td>\n",
       "      <td>3.645420</td>\n",
       "      <td>3.765457</td>\n",
       "      <td>3.743147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA</th>\n",
       "      <td>4.080457</td>\n",
       "      <td>3.975034</td>\n",
       "      <td>3.822957</td>\n",
       "      <td>4.000099</td>\n",
       "      <td>3.766290</td>\n",
       "      <td>3.643913</td>\n",
       "      <td>3.698537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FL</th>\n",
       "      <td>4.080649</td>\n",
       "      <td>4.074173</td>\n",
       "      <td>3.898609</td>\n",
       "      <td>4.011874</td>\n",
       "      <td>3.814655</td>\n",
       "      <td>3.843314</td>\n",
       "      <td>3.717402</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  OR        BC        OH        TX        GA        MA  \\\n",
       "user_state                                                               \n",
       "OR          3.866465  3.956460  3.757039  4.001287  3.708206  3.802630   \n",
       "BC          4.015150  3.607017  4.000000  3.968843  3.635731  3.760193   \n",
       "OH          4.052720  4.077957  3.688640  3.937296  3.715139  3.833462   \n",
       "TX          4.088185  4.008251  3.902278  3.822535  3.736767  3.811718   \n",
       "GA          4.078620  3.932990  3.708677  3.979075  3.645420  3.765457   \n",
       "MA          4.080457  3.975034  3.822957  4.000099  3.766290  3.643913   \n",
       "FL          4.080649  4.074173  3.898609  4.011874  3.814655  3.843314   \n",
       "\n",
       "                  FL  \n",
       "user_state            \n",
       "OR          3.692002  \n",
       "BC          3.731510  \n",
       "OH          3.749846  \n",
       "TX          3.688064  \n",
       "GA          3.743147  \n",
       "MA          3.698537  \n",
       "FL          3.717402  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_ubs = pd_ubs.set_index(\"user_state\")\n",
    "pd_ubs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "caf7d105",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "h = sns.heatmap(pd_ubs, annot=True, fmt=\".1f\", cmap=\"BuPu\")\n",
    "fig = h.get_figure()\n",
    "fig.savefig(\"ubs.png\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "efe17c7b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8503269f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "PySpark",
   "language": "python",
   "name": "pyspark"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}