Section 6-27 Python for Data Analysis - DataFrames Part 1.ipynb

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   "source":[
    "# Pandas - DataFrames"
   ],
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   "cell_type":"code",
   "source":[
    "import numpy as np\n",
    "import pandas as pd"
   ],
   "execution_count":43,
   "outputs":[
    
   ],
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   "source":[
    "from numpy.random import randn"
   ],
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    "np.random.seed(101)"
   ],
   "execution_count":45,
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   "source":[
    "df = pd.DataFrame(randn(5,4), ['A', 'B', 'C', 'D', 'E'], ['W', 'X', 'Y', 'Z'])"
   ],
   "execution_count":46,
   "outputs":[
    
   ],
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       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th><\/th>\n",
       "      <th>W<\/th>\n",
       "      <th>X<\/th>\n",
       "      <th>Y<\/th>\n",
       "      <th>Z<\/th>\n",
       "    <\/tr>\n",
       "  <\/thead>\n",
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       "      <td>2.706850<\/td>\n",
       "      <td>0.628133<\/td>\n",
       "      <td>0.907969<\/td>\n",
       "      <td>0.503826<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>B<\/th>\n",
       "      <td>0.651118<\/td>\n",
       "      <td>-0.319318<\/td>\n",
       "      <td>-0.848077<\/td>\n",
       "      <td>0.605965<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>C<\/th>\n",
       "      <td>-2.018168<\/td>\n",
       "      <td>0.740122<\/td>\n",
       "      <td>0.528813<\/td>\n",
       "      <td>-0.589001<\/td>\n",
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       "      <th>D<\/th>\n",
       "      <td>0.188695<\/td>\n",
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       "      <td>-0.933237<\/td>\n",
       "      <td>0.955057<\/td>\n",
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       "      <th>E<\/th>\n",
       "      <td>0.190794<\/td>\n",
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       "      <td>2.605967<\/td>\n",
       "      <td>0.683509<\/td>\n",
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    "df['W']"
   ],
   "execution_count":48,
   "outputs":[
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       "<pre>A    2.706850\n",
       "B    0.651118\n",
       "C   -2.018168\n",
       "D    0.188695\n",
       "E    0.190794\n",
       "Name: W, dtype: float64<\/pre>"
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   "source":[
    "type(df['W'])"
   ],
   "execution_count":49,
   "outputs":[
    {
     "data":{
      "text\/plain":[
       "pandas.core.series.Series"
      ]
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     },
     "output_type":"display_data"
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   "source":[
    "type(df)"
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   "execution_count":50,
   "outputs":[
    {
     "data":{
      "text\/plain":[
       "pandas.core.frame.DataFrame"
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     },
     "output_type":"display_data"
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    "df.W"
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   "execution_count":51,
   "outputs":[
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       "<pre>A    2.706850\n",
       "B    0.651118\n",
       "C   -2.018168\n",
       "D    0.188695\n",
       "E    0.190794\n",
       "Name: W, dtype: float64<\/pre>"
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   "source":[
    "df[['W', 'Z']]"
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   "execution_count":52,
   "outputs":[
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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>W<\/th>\n",
       "      <th>Z<\/th>\n",
       "    <\/tr>\n",
       "  <\/thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A<\/th>\n",
       "      <td>2.706850<\/td>\n",
       "      <td>0.503826<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>B<\/th>\n",
       "      <td>0.651118<\/td>\n",
       "      <td>0.605965<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>C<\/th>\n",
       "      <td>-2.018168<\/td>\n",
       "      <td>-0.589001<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>D<\/th>\n",
       "      <td>0.188695<\/td>\n",
       "      <td>0.955057<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>E<\/th>\n",
       "      <td>0.190794<\/td>\n",
       "      <td>0.683509<\/td>\n",
       "    <\/tr>\n",
       "  <\/tbody>\n",
       "<\/table>\n",
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   "source":[
    "df['new'] = df['W'] + df['Y']"
   ],
   "execution_count":53,
   "outputs":[
    
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   "execution_count":54,
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       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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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>W<\/th>\n",
       "      <th>X<\/th>\n",
       "      <th>Y<\/th>\n",
       "      <th>Z<\/th>\n",
       "      <th>new<\/th>\n",
       "    <\/tr>\n",
       "  <\/thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A<\/th>\n",
       "      <td>2.706850<\/td>\n",
       "      <td>0.628133<\/td>\n",
       "      <td>0.907969<\/td>\n",
       "      <td>0.503826<\/td>\n",
       "      <td>3.614819<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>B<\/th>\n",
       "      <td>0.651118<\/td>\n",
       "      <td>-0.319318<\/td>\n",
       "      <td>-0.848077<\/td>\n",
       "      <td>0.605965<\/td>\n",
       "      <td>-0.196959<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>C<\/th>\n",
       "      <td>-2.018168<\/td>\n",
       "      <td>0.740122<\/td>\n",
       "      <td>0.528813<\/td>\n",
       "      <td>-0.589001<\/td>\n",
       "      <td>-1.489355<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>D<\/th>\n",
       "      <td>0.188695<\/td>\n",
       "      <td>-0.758872<\/td>\n",
       "      <td>-0.933237<\/td>\n",
       "      <td>0.955057<\/td>\n",
       "      <td>-0.744542<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>E<\/th>\n",
       "      <td>0.190794<\/td>\n",
       "      <td>1.978757<\/td>\n",
       "      <td>2.605967<\/td>\n",
       "      <td>0.683509<\/td>\n",
       "      <td>2.796762<\/td>\n",
       "    <\/tr>\n",
       "  <\/tbody>\n",
       "<\/table>\n",
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    "# drop column\n",
    "# axis - why rows is 0 and column is 1\n",
    "# reference comes back to numpy since dataframes are essentially a fancy index markers on top of numpy array\n",
    "df.drop('new', axis=1, inplace=True)"
   ],
   "execution_count":55,
   "outputs":[
    
   ],
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       "    .dataframe tbody tr th {\n",
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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>W<\/th>\n",
       "      <th>X<\/th>\n",
       "      <th>Y<\/th>\n",
       "      <th>Z<\/th>\n",
       "    <\/tr>\n",
       "  <\/thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A<\/th>\n",
       "      <td>2.706850<\/td>\n",
       "      <td>0.628133<\/td>\n",
       "      <td>0.907969<\/td>\n",
       "      <td>0.503826<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>B<\/th>\n",
       "      <td>0.651118<\/td>\n",
       "      <td>-0.319318<\/td>\n",
       "      <td>-0.848077<\/td>\n",
       "      <td>0.605965<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>C<\/th>\n",
       "      <td>-2.018168<\/td>\n",
       "      <td>0.740122<\/td>\n",
       "      <td>0.528813<\/td>\n",
       "      <td>-0.589001<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>D<\/th>\n",
       "      <td>0.188695<\/td>\n",
       "      <td>-0.758872<\/td>\n",
       "      <td>-0.933237<\/td>\n",
       "      <td>0.955057<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>E<\/th>\n",
       "      <td>0.190794<\/td>\n",
       "      <td>1.978757<\/td>\n",
       "      <td>2.605967<\/td>\n",
       "      <td>0.683509<\/td>\n",
       "    <\/tr>\n",
       "  <\/tbody>\n",
       "<\/table>\n",
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   "cell_type":"code",
   "source":[
    "# drop row\n",
    "df.drop('E')"
   ],
   "execution_count":35,
   "outputs":[
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th><\/th>\n",
       "      <th>W<\/th>\n",
       "      <th>X<\/th>\n",
       "      <th>Y<\/th>\n",
       "      <th>Z<\/th>\n",
       "    <\/tr>\n",
       "  <\/thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A<\/th>\n",
       "      <td>2.706850<\/td>\n",
       "      <td>0.628133<\/td>\n",
       "      <td>0.907969<\/td>\n",
       "      <td>0.503826<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>B<\/th>\n",
       "      <td>0.651118<\/td>\n",
       "      <td>-0.319318<\/td>\n",
       "      <td>-0.848077<\/td>\n",
       "      <td>0.605965<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>C<\/th>\n",
       "      <td>-2.018168<\/td>\n",
       "      <td>0.740122<\/td>\n",
       "      <td>0.528813<\/td>\n",
       "      <td>-0.589001<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>D<\/th>\n",
       "      <td>0.188695<\/td>\n",
       "      <td>-0.758872<\/td>\n",
       "      <td>-0.933237<\/td>\n",
       "      <td>0.955057<\/td>\n",
       "    <\/tr>\n",
       "  <\/tbody>\n",
       "<\/table>\n",
       "<\/div>"
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    "df"
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   "execution_count":36,
   "outputs":[
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th><\/th>\n",
       "      <th>W<\/th>\n",
       "      <th>X<\/th>\n",
       "      <th>Y<\/th>\n",
       "      <th>Z<\/th>\n",
       "    <\/tr>\n",
       "  <\/thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A<\/th>\n",
       "      <td>2.706850<\/td>\n",
       "      <td>0.628133<\/td>\n",
       "      <td>0.907969<\/td>\n",
       "      <td>0.503826<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>B<\/th>\n",
       "      <td>0.651118<\/td>\n",
       "      <td>-0.319318<\/td>\n",
       "      <td>-0.848077<\/td>\n",
       "      <td>0.605965<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>C<\/th>\n",
       "      <td>-2.018168<\/td>\n",
       "      <td>0.740122<\/td>\n",
       "      <td>0.528813<\/td>\n",
       "      <td>-0.589001<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>D<\/th>\n",
       "      <td>0.188695<\/td>\n",
       "      <td>-0.758872<\/td>\n",
       "      <td>-0.933237<\/td>\n",
       "      <td>0.955057<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>E<\/th>\n",
       "      <td>0.190794<\/td>\n",
       "      <td>1.978757<\/td>\n",
       "      <td>2.605967<\/td>\n",
       "      <td>0.683509<\/td>\n",
       "    <\/tr>\n",
       "  <\/tbody>\n",
       "<\/table>\n",
       "<\/div>"
      ]
     },
     "metadata":{
      
     },
     "output_type":"display_data"
    }
   ],
   "metadata":{
    "datalore":{
     "node_id":"hlGqVnSwJhcp1me01cn0f2",
     "type":"CODE",
     "hide_input_from_viewers":true,
     "hide_output_from_viewers":true
    }
   }
  },
  {
   "cell_type":"code",
   "source":[
    "# (5, 4) rows is 0 axis while y is 1 axis\n",
    "df.shape"
   ],
   "execution_count":37,
   "outputs":[
    {
     "data":{
      "text\/plain":[
       "(5, 4)"
      ]
     },
     "metadata":{
      
     },
     "output_type":"display_data"
    }
   ],
   "metadata":{
    "datalore":{
     "node_id":"dVLrUyOpP3FsOGpnWuQcSB",
     "type":"CODE",
     "hide_input_from_viewers":true,
     "hide_output_from_viewers":true
    }
   }
  },
  {
   "cell_type":"code",
   "source":[
    "# selecting rows\n",
    "df"
   ],
   "execution_count":39,
   "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>W<\/th>\n",
       "      <th>X<\/th>\n",
       "      <th>Y<\/th>\n",
       "      <th>Z<\/th>\n",
       "    <\/tr>\n",
       "  <\/thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A<\/th>\n",
       "      <td>2.706850<\/td>\n",
       "      <td>0.628133<\/td>\n",
       "      <td>0.907969<\/td>\n",
       "      <td>0.503826<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>B<\/th>\n",
       "      <td>0.651118<\/td>\n",
       "      <td>-0.319318<\/td>\n",
       "      <td>-0.848077<\/td>\n",
       "      <td>0.605965<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>C<\/th>\n",
       "      <td>-2.018168<\/td>\n",
       "      <td>0.740122<\/td>\n",
       "      <td>0.528813<\/td>\n",
       "      <td>-0.589001<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>D<\/th>\n",
       "      <td>0.188695<\/td>\n",
       "      <td>-0.758872<\/td>\n",
       "      <td>-0.933237<\/td>\n",
       "      <td>0.955057<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>E<\/th>\n",
       "      <td>0.190794<\/td>\n",
       "      <td>1.978757<\/td>\n",
       "      <td>2.605967<\/td>\n",
       "      <td>0.683509<\/td>\n",
       "    <\/tr>\n",
       "  <\/tbody>\n",
       "<\/table>\n",
       "<\/div>"
      ]
     },
     "metadata":{
      
     },
     "output_type":"display_data"
    }
   ],
   "metadata":{
    "datalore":{
     "node_id":"4HFRQ2RfrpLEN2eph837cD",
     "type":"CODE",
     "hide_input_from_viewers":true,
     "hide_output_from_viewers":true
    }
   }
  },
  {
   "cell_type":"code",
   "source":[
    "df.loc['C']"
   ],
   "execution_count":41,
   "outputs":[
    {
     "data":{
      "text\/html":[
       "<pre>W   -2.018168\n",
       "X    0.740122\n",
       "Y    0.528813\n",
       "Z   -0.589001\n",
       "Name: C, dtype: float64<\/pre>"
      ]
     },
     "metadata":{
      
     },
     "output_type":"display_data"
    }
   ],
   "metadata":{
    "datalore":{
     "node_id":"e2meGZkOQGCkypi5DLoqve",
     "type":"CODE",
     "hide_input_from_viewers":true,
     "hide_output_from_viewers":true
    }
   }
  },
  {
   "cell_type":"code",
   "source":[
    "df.iloc[2]"
   ],
   "execution_count":42,
   "outputs":[
    {
     "data":{
      "text\/html":[
       "<pre>W   -2.018168\n",
       "X    0.740122\n",
       "Y    0.528813\n",
       "Z   -0.589001\n",
       "Name: C, dtype: float64<\/pre>"
      ]
     },
     "metadata":{
      
     },
     "output_type":"display_data"
    }
   ],
   "metadata":{
    "datalore":{
     "node_id":"Ybk8c8Djcd5I9h3WNdwOtD",
     "type":"CODE",
     "hide_input_from_viewers":true,
     "hide_output_from_viewers":true
    }
   }
  },
  {
   "cell_type":"code",
   "source":[
    "# [row, column]\n",
    "df.loc['B', 'Y']"
   ],
   "execution_count":56,
   "outputs":[
    {
     "data":{
      "text\/plain":[
       "-0.8480769834036315"
      ]
     },
     "metadata":{
      
     },
     "output_type":"display_data"
    }
   ],
   "metadata":{
    "datalore":{
     "node_id":"3pqh4iBup9400dlst3urh0",
     "type":"CODE",
     "hide_input_from_viewers":true,
     "hide_output_from_viewers":true
    }
   }
  },
  {
   "cell_type":"code",
   "source":[
    "df.loc[['A', 'B'], ['W', 'Y']]"
   ],
   "execution_count":57,
   "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>W<\/th>\n",
       "      <th>Y<\/th>\n",
       "    <\/tr>\n",
       "  <\/thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A<\/th>\n",
       "      <td>2.706850<\/td>\n",
       "      <td>0.907969<\/td>\n",
       "    <\/tr>\n",
       "    <tr>\n",
       "      <th>B<\/th>\n",
       "      <td>0.651118<\/td>\n",
       "      <td>-0.848077<\/td>\n",
       "    <\/tr>\n",
       "  <\/tbody>\n",
       "<\/table>\n",
       "<\/div>"
      ]
     },
     "metadata":{
      
     },
     "output_type":"display_data"
    }
   ],
   "metadata":{
    "datalore":{
     "node_id":"lTIgI1vUferV4ic1pqiz4B",
     "type":"CODE",
     "hide_input_from_viewers":true,
     "hide_output_from_viewers":true
    }
   }
  },
  {
   "cell_type":"code",
   "source":[
    
   ],
   "execution_count":null,
   "outputs":[
    
   ],
   "metadata":{
    "datalore":{
     "node_id":"zjVZCsAoSDGnF39AGJNwU7",
     "type":"CODE",
     "hide_input_from_viewers":true,
     "hide_output_from_viewers":true
    }
   }
  }
 ],
 "metadata":{
  "kernelspec":{
   "display_name":"Python",
   "language":"python",
   "name":"python"
  },
  "datalore":{
   "computation_mode":"JUPYTER",
   "package_manager":"pip",
   "base_environment":"default",
   "packages":[
    
   ],
   "report_row_ids":[
    
   ],
   "version":3
  }
 },
 "nbformat":4,
 "nbformat_minor":4
}