From 56db2c5003fde0579c9e9821de853593f3b9eb62 Mon Sep 17 00:00:00 2001 From: pw4e8vz7f <2907813330@qq.com> Date: Fri, 15 Apr 2022 23:45:14 +0800 Subject: [PATCH] ADD file via upload --- ...制箱形图分析北京天气数据.ipynb | 428 ++++++++++++++++++ 1 file changed, 428 insertions(+) create mode 100644 何海鹏—— Python绘制箱形图分析北京天气数据.ipynb diff --git a/何海鹏—— Python绘制箱形图分析北京天气数据.ipynb b/何海鹏—— Python绘制箱形图分析北京天气数据.ipynb new file mode 100644 index 0000000..36a9916 --- /dev/null +++ b/何海鹏—— Python绘制箱形图分析北京天气数据.ipynb @@ -0,0 +1,428 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Python绘制箱形图分析北京天气数据" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 箱形图\n", + "箱形图（Box-plot）又称为盒须图、盒式图或箱线图，是一种用作显示一组数据***分散情况***的统计图。\n", + "\n", + "#### 箱形图的图形组成\n", + "对于一组数字，先将其从小到达排列，然后计算图中元素：\n", + "\n", + "\n", + "#### 箱形图的价值\n", + "1. 直观明了地识别数据中的异常值\n", + "2. 利用箱线图判断数据的偏态和尾重\n", + "3. 利用箱线图比较几批数据的形状" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import seaborn as sns\n", + "sns.set(style=\"whitegrid\")\n", + "sns.set(rc={'figure.figsize':(11.7,8.27)})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "实例目标：对比北京2019年天气数据中，4个季度的温度分布对比" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 1. 读取北京天气数据" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv(\"./datas/beijing_tianqi/beijing_tianqi_2019.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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ymdbWenduyWendutianqifengxiangfengliaqiaqiInfoaqiLevel
02019-01-011℃-10℃晴~多云西北风1级56良2
12019-01-021℃-9℃多云东北风1级60良2
22019-01-032℃-7℃霾东北风1级165中度污染4
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" + ], + "text/plain": [ + " ymd bWendu yWendu tianqi fengxiang fengli aqi aqiInfo aqiLevel\n", + "0 2019-01-01 1℃ -10℃ 晴~多云 西北风 1级 56 良 2\n", + "1 2019-01-02 1℃ -9℃ 多云 东北风 1级 60 良 2\n", + "2 2019-01-03 2℃ -7℃ 霾 东北风 1级 165 中度污染 4" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head(3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2. 把温度列从字符串变成数字" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# 把最高温度列，从2℃的形式，变成数字\n", + "df[\"bWendu\"] = df[\"bWendu\"].str.replace(\"℃\", \"\").astype(float)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 365 entries, 0 to 364\n", + "Data columns (total 9 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 ymd 365 non-null object \n", + " 1 bWendu 365 non-null float64\n", + " 2 yWendu 365 non-null object \n", + " 3 tianqi 365 non-null object \n", + " 4 fengxiang 365 non-null object \n", + " 5 fengli 365 non-null object \n", + " 6 aqi 365 non-null int64 \n", + " 7 aqiInfo 365 non-null object \n", + " 8 aqiLevel 365 non-null int64 \n", + "dtypes: float64(1), int64(2), object(6)\n", + "memory usage: 25.8+ KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3. 根据天日期添加季度数字列" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# 获取季度数字\n", + "df[\"quarter\"] = pd.to_datetime(df[\"ymd\"]).dt.quarter" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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ymdbWenduyWendutianqifengxiangfengliaqiaqiInfoaqiLevelquarter
02019-01-011.0-10℃晴~多云西北风1级56良21
12019-01-021.0-9℃多云东北风1级60良21
22019-01-032.0-7℃霾东北风1级165中度污染41
32019-01-042.0-7℃晴西北风2级50优11
42019-01-050.0-8℃多云东北风2级29优11
52019-01-063.0-7℃多云东南风1级84良21
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" + ], + "text/plain": [ + " ymd bWendu yWendu tianqi fengxiang fengli aqi aqiInfo aqiLevel \\\n", + "0 2019-01-01 1.0 -10℃ 晴~多云 西北风 1级 56 良 2 \n", + "1 2019-01-02 1.0 -9℃ 多云 东北风 1级 60 良 2 \n", + "2 2019-01-03 2.0 -7℃ 霾 东北风 1级 165 中度污染 4 \n", + "3 2019-01-04 2.0 -7℃ 晴 西北风 2级 50 优 1 \n", + "4 2019-01-05 0.0 -8℃ 多云 东北风 2级 29 优 1 \n", + "5 2019-01-06 3.0 -7℃ 多云 东南风 1级 84 良 2 \n", + "\n", + " quarter \n", + "0 1 \n", + "1 1 \n", + "2 1 \n", + "3 1 \n", + "4 1 \n", + "5 1 " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head(6)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 4. 调用seaborn绘制boxplot" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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