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Learn more about bidirectional Unicode charactersOriginal file line number Diff line number Diff line change @@ -0,0 +1,347 @@ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Pandas DataFrame Views" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style>\n", " .dataframe thead tr:only-child th {\n", " text-align: right;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: left;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>A</th>\n", " <th>B</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>0.557771</td>\n", " <td>0.260547</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>0.016835</td>\n", " <td>0.656023</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>0.564032</td>\n", " <td>0.094023</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>0.163993</td>\n", " <td>0.473556</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>0.026951</td>\n", " <td>0.899029</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " A B\n", "0 0.557771 0.260547\n", "1 0.016835 0.656023\n", "2 0.564032 0.094023\n", "3 0.163993 0.473556\n", "4 0.026951 0.899029" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = pd.DataFrame(np.random.rand(100, 2), columns=['A', 'B'])\n", "df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This doesn't work because the first line returns a view of the DataFrame, not a copy, and the behavior of assignment to views is undefined." ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/das/Anaconda/lib/python3.6/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n", " \n" ] } ], "source": [ "df_new = df[df.A < 0.5]\n", "df_new['C'] = df_new['B'] + 1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If we explicitly specify the columns and use `.loc[]` we get a copy which we can assign to:" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style>\n", " .dataframe thead tr:only-child th {\n", " text-align: right;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: left;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>A</th>\n", " <th>B</th>\n", " <th>C</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>1</th>\n", " <td>0.016835</td>\n", " <td>0.656023</td>\n", " <td>1.656023</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>0.163993</td>\n", " <td>0.473556</td>\n", " <td>1.473556</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>0.026951</td>\n", " <td>0.899029</td>\n", " <td>1.899029</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>0.145798</td>\n", " <td>0.533323</td>\n", " <td>1.533323</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>0.448204</td>\n", " <td>0.139057</td>\n", " <td>1.139057</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " A B C\n", "1 0.016835 0.656023 1.656023\n", "3 0.163993 0.473556 1.473556\n", "4 0.026951 0.899029 1.899029\n", "5 0.145798 0.533323 1.533323\n", "6 0.448204 0.139057 1.139057" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_new = df.loc[df.A < 0.5, ['A', 'B']]\n", "df_new['C'] = df_new['B'] + 1\n", "df_new.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alternatively one can use the `assign()` method to assign a new column to the DataFrame. This is also shorter:" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style>\n", " .dataframe thead tr:only-child th {\n", " text-align: right;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: left;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>A</th>\n", " <th>B</th>\n", " <th>C</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>1</th>\n", " <td>0.016835</td>\n", " <td>0.656023</td>\n", " <td>1.656023</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>0.163993</td>\n", " <td>0.473556</td>\n", " <td>1.473556</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>0.026951</td>\n", " <td>0.899029</td>\n", " <td>1.899029</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>0.145798</td>\n", " <td>0.533323</td>\n", " <td>1.533323</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>0.448204</td>\n", " <td>0.139057</td>\n", " <td>1.139057</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " A B C\n", "1 0.016835 0.656023 1.656023\n", "3 0.163993 0.473556 1.473556\n", "4 0.026951 0.899029 1.899029\n", "5 0.145798 0.533323 1.533323\n", "6 0.448204 0.139057 1.139057" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_new = df[df.A < 0.5].assign(C=lambda x: x.B + 1)\n", "df_new.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.3" } }, "nbformat": 4, "nbformat_minor": 2 }