From deef1b74dbcc3bc02831ec4178b7049b5b7d6db7 Mon Sep 17 00:00:00 2001 From: 100gle <569590461@qq.com> Date: Thu, 30 Jun 2022 09:04:07 +0800 Subject: [PATCH] =?UTF-8?q?feat:=20=E6=96=B0=E5=A2=9EVol18=E7=AB=A0?= =?UTF-8?q?=E8=8A=82=E7=A4=BA=E4=BE=8B=E6=BA=90=E7=A0=81?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- code/18/pandas_advanced_tricks.ipynb | 2464 ++++++++++++++++++++++++++ code/18/plot.ipynb | 460 +++++ data/python-logo-master-v3-TM.png | Bin 0 -> 83564 bytes 3 files changed, 2924 insertions(+) create mode 100644 code/18/pandas_advanced_tricks.ipynb create mode 100644 code/18/plot.ipynb create mode 100644 data/python-logo-master-v3-TM.png diff --git a/code/18/pandas_advanced_tricks.ipynb b/code/18/pandas_advanced_tricks.ipynb new file mode 100644 index 0000000..3ed3f67 --- /dev/null +++ b/code/18/pandas_advanced_tricks.ipynb @@ -0,0 +1,2464 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "collapsed": true, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# applymap" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
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uidpidcodeis_vip
01O1_OTrue
12L2_LTrue
23k3_kFalse
34F4_FTrue
45Z5_ZTrue
56u6_uFalse
67t7_tFalse
78V8_VTrue
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PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
0103Braund, Mr. Owen Harrismale22.010A/5 211717.2500NaNS
1211Cumings, Mrs. John Bradley (Florence Briggs Th...female38.010PC 1759971.2833C85C
2313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250NaNS
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000C123S
4503Allen, Mr. William Henrymale35.0003734508.0500NaNS
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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "titanic[\"Sex\"].value_counts().plot.bar()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[Text(0, 0, 'male'), Text(1, 0, 'female')]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/svg+xml": "\n\n\n \n \n \n \n 2022-06-30T09:00:52.523775\n image/svg+xml\n \n \n Matplotlib v3.5.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "ax = titanic[\"Sex\"].value_counts().plot.bar()\n", + "ax.set_title(\"The Bar Chart of Sex\")\n", + "ax.set_xlabel(\"Sex\")\n", + "ax.set_ylabel(\"Counter\")\n", + "ax.set_xticklabels([\"male\", \"female\"], rotation=0)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/svg+xml": "\n\n\n \n \n \n \n 2022-06-30T09:00:52.623399\n image/svg+xml\n \n \n Matplotlib v3.5.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "titanic[\"Sex\"].value_counts().plot.pie()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/svg+xml": "\n\n\n \n \n \n \n 2022-06-30T09:00:52.733823\n image/svg+xml\n \n \n Matplotlib v3.5.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "titanic[\"Sex\"].value_counts().plot.bar(\n", + " figsize=(8, 6),\n", + " title=\"The Bar Chart of Sex\",\n", + " rot=45,\n", + " xlabel=\"Sex\",\n", + " ylabel=\"Number\",\n", + " ylim=(0, 550),\n", + " legend=True,\n", + " fontsize=8.5,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/svg+xml": "\n\n\n \n \n \n \n 2022-06-30T09:00:52.860825\n image/svg+xml\n \n \n Matplotlib v3.5.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from matplotlib import image\n", + "from matplotlib.offsetbox import OffsetImage\n", + "\n", + "\n", + "logo = image.imread(\"../../data/python-logo-master-v3-TM.png\")\n", + "\n", + "ax = titanic[\"Sex\"].value_counts().plot.pie(\n", + " figsize=(6, 8),\n", + " ylabel=\"\",\n", + " title=\"The Pie Chart of Sex\",\n", + " explode=(0, 0.05),\n", + " autopct=lambda pct: f\"{round(pct, 2)}%\",\n", + " pctdistance=0.4,\n", + " shadow=True,\n", + " colors=(\"steelblue\", \"orange\"),\n", + ")\n", + "\n", + "for n, tx in enumerate(ax.texts):\n", + " if (n+1) % 2==0:\n", + " tx.set_color(\"white\")\n", + "\n", + "logo_image = OffsetImage(logo, zoom=.5)\n", + "logo_image.set_offset((35, 25))\n", + "ax.add_artist(logo_image)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [] + } + ], + 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