{"id":1044934,"date":"2024-12-31T13:18:50","date_gmt":"2024-12-31T05:18:50","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1044934.html"},"modified":"2024-12-31T13:18:54","modified_gmt":"2024-12-31T05:18:54","slug":"python%e5%a6%82%e4%bd%95%e8%bf%9b%e8%a1%8c%e6%95%b0%e6%8d%ae%e7%ad%9b%e9%80%89%e7%94%bb%e5%9b%be","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1044934.html","title":{"rendered":"Python\u5982\u4f55\u8fdb\u884c\u6570\u636e\u7b5b\u9009\u753b\u56fe"},"content":{"rendered":"

\"Python\u5982\u4f55\u8fdb\u884c\u6570\u636e\u7b5b\u9009\u753b\u56fe\"<\/p>\n

Python\u8fdb\u884c\u6570\u636e\u7b5b\u9009\u548c\u753b\u56fe\u7684\u65b9\u6cd5\u4e3b\u8981\u5305\u62ec\u4ee5\u4e0b\u6b65\u9aa4\uff1a\u5bfc\u5165\u5fc5\u8981\u7684\u5e93\u3001\u8bfb\u53d6\u548c\u7b5b\u9009\u6570\u636e\u3001\u8fdb\u884c\u6570\u636e\u5206\u6790\u3001\u521b\u5efa\u53ef\u89c6\u5316\u56fe\u8868\u3002\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Pandas\u3001Matplotlib\u548cSeaborn\u7b49\u5e93\u6765\u5b9e\u73b0\u8fd9\u4e9b\u4efb\u52a1\u3002<\/strong><\/p>\n<\/p>\n

\u4e00\u3001\u5bfc\u5165\u5fc5\u8981\u7684\u5e93<\/p>\n<\/p>\n

\u5728\u5f00\u59cb\u6570\u636e\u7b5b\u9009\u548c\u7ed8\u56fe\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u5148\u5bfc\u5165\u4e00\u4e9bPython\u5e93\u3002\u5e38\u7528\u7684\u5e93\u5305\u62ecPandas\u7528\u4e8e\u6570\u636e\u5904\u7406\uff0cMatplotlib\u548cSeaborn\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n

import pandas as pd<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import seaborn as sns<\/p>\n
<\/code><\/pre>\n<\/p>\n
Pandas\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5de5\u5177\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\u3002Matplotlib\u662f\u4e00\u4e2a2D\u7ed8\u56fe\u5e93\uff0c\u5b83\u53ef\u4ee5\u751f\u6210\u56fe\u5f62\uff0c\u5305\u62ec\u56fe\u8868\u3001\u56fe\u5f62\u548c\u5176\u4ed6\u590d\u6742\u7684\u4e8c\u7ef4\u56fe\u5f62\u3002Seaborn\u662f\u4e00\u4e2a\u57fa\u4e8eMatplotlib\u7684Python\u6570\u636e\u53ef\u89c6\u5316\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u66f4\u9ad8\u7ea7\u7684\u63a5\u53e3\u6765\u751f\u6210\u5438\u5f15\u4eba\u7684\u548c\u4fe1\u606f\u4e30\u5bcc\u7684\u7edf\u8ba1\u56fe\u8868\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u8bfb\u53d6\u548c\u7b5b\u9009\u6570\u636e<\/p>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u9700\u8981\u8bfb\u53d6\u6570\u636e\u5e76\u8fdb\u884c\u7b5b\u9009\u3002Pandas\u63d0\u4f9b\u4e86\u8bb8\u591a\u65b9\u6cd5\u6765\u8bfb\u53d6\u6570\u636e\u6587\u4ef6\uff0c\u4f8b\u5982CSV\u3001Excel\u6587\u4ef6\u7b49\u3002\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2aCSV\u6587\u4ef6\u5305\u542b\u67d0\u4e9b\u6570\u636e\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Pandas\u7684read_csv<\/code>\u65b9\u6cd5\u6765\u8bfb\u53d6\u6570\u636e\uff1a<\/p>\n<\/p>\n
# \u8bfb\u53d6CSV\u6587\u4ef6<\/p>\n
df = pd.read_csv('data.csv')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e00\u65e6\u6570\u636e\u88ab\u8bfb\u53d6\u5230\u4e00\u4e2aDataFrame\u4e2d\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u4f7f\u7528Pandas\u7684\u5404\u79cd\u65b9\u6cd5\u5bf9\u6570\u636e\u8fdb\u884c\u7b5b\u9009\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u9009\u62e9\u7279\u5b9a\u7684\u5217\u3001\u7b5b\u9009\u7279\u5b9a\u7684\u884c\u3001\u8fc7\u6ee4\u6389\u7f3a\u5931\u503c\u7b49\u3002<\/p>\n<\/p>\n
# \u7b5b\u9009\u7279\u5b9a\u7684\u5217<\/p>\n
df_filtered = df[['column1', 'column2', 'column3']]<\/p>\n
\u7b5b\u9009\u6ee1\u8db3\u6761\u4ef6\u7684\u884c<\/strong><\/h2>\n
df_filtered = df[df['column1'] > 50]<\/p>\n
\u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c<\/strong><\/h2>\n
df_filtered = df.dropna()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u8fdb\u884c\u6570\u636e\u5206\u6790<\/p>\n<\/p>\n
\u5728\u5bf9\u6570\u636e\u8fdb\u884c\u7b5b\u9009\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u8fdb\u884c\u4e00\u4e9b\u57fa\u672c\u7684\u6570\u636e\u5206\u6790\u3002Pandas\u63d0\u4f9b\u4e86\u8bb8\u591a\u65b9\u6cd5\u6765\u8ba1\u7b97\u7edf\u8ba1\u91cf\uff0c\u4f8b\u5982\u5747\u503c\u3001\u4e2d\u4f4d\u6570\u3001\u6807\u51c6\u5dee\u7b49\u3002<\/p>\n<\/p>\n
# \u8ba1\u7b97\u5747\u503c<\/p>\n
mean_value = df_filtered['column1'].mean()<\/p>\n
\u8ba1\u7b97\u4e2d\u4f4d\u6570<\/strong><\/h2>\n
median_value = df_filtered['column1'].median()<\/p>\n
\u8ba1\u7b97\u6807\u51c6\u5dee<\/strong><\/h2>\n
std_value = df_filtered['column1'].std()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u4e9b\u7edf\u8ba1\u91cf\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u4e86\u89e3\u6570\u636e\u7684\u5206\u5e03\u548c\u8d8b\u52bf\uff0c\u4ece\u800c\u66f4\u597d\u5730\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n
\u56db\u3001\u521b\u5efa\u53ef\u89c6\u5316\u56fe\u8868<\/p>\n<\/p>\n
\u73b0\u5728\uff0c\u6211\u4eec\u5df2\u7ecf\u7b5b\u9009\u5e76\u5206\u6790\u4e86\u6570\u636e\uff0c\u63a5\u4e0b\u6765\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Matplotlib\u548cSeaborn\u6765\u521b\u5efa\u56fe\u8868\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u7528\u7684\u56fe\u8868\u7c7b\u578b\u53ca\u5176\u521b\u5efa\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n
    \n
  1. \u6298\u7ebf\u56fe\uff08Line Plot\uff09<\/strong><\/li>\n<\/ol>\n
    \u6298\u7ebf\u56fe\u9002\u7528\u4e8e\u663e\u793a\u6570\u636e\u968f\u65f6\u95f4\u7684\u53d8\u5316\u8d8b\u52bf\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Matplotlib\u7684plot<\/code>\u65b9\u6cd5\u6765\u521b\u5efa\u6298\u7ebf\u56fe\u3002<\/p>\n<\/p>\n
    plt.figure(figsize=(10, 6))<\/p>\n
    plt.plot(df_filtered['column1'], df_filtered['column2'])<\/p>\n
    plt.xlabel('X\u8f74\u6807\u7b7e')<\/p>\n
    plt.ylabel('Y\u8f74\u6807\u7b7e')<\/p>\n
    plt.title('\u6298\u7ebf\u56fe\u6807\u9898')<\/p>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
      \n
    1. \u67f1\u72b6\u56fe\uff08Bar Plot\uff09<\/strong><\/li>\n<\/ol>\n
      \u67f1\u72b6\u56fe\u9002\u7528\u4e8e\u6bd4\u8f83\u4e0d\u540c\u7c7b\u522b\u7684\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Matplotlib\u7684bar<\/code>\u65b9\u6cd5\u6765\u521b\u5efa\u67f1\u72b6\u56fe\u3002<\/p>\n<\/p>\n
      plt.figure(figsize=(10, 6))<\/p>\n
      plt.bar(df_filtered['column1'], df_filtered['column2'])<\/p>\n
      plt.xlabel('X\u8f74\u6807\u7b7e')<\/p>\n
      plt.ylabel('Y\u8f74\u6807\u7b7e')<\/p>\n
      plt.title('\u67f1\u72b6\u56fe\u6807\u9898')<\/p>\n
      plt.show()<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      Seaborn\u4e5f\u63d0\u4f9b\u4e86\u521b\u5efa\u67f1\u72b6\u56fe\u7684\u9ad8\u7ea7\u63a5\u53e3\uff1a<\/p>\n<\/p>\n
      plt.figure(figsize=(10, 6))<\/p>\n
      sns.barplot(x='column1', y='column2', data=df_filtered)<\/p>\n
      plt.xlabel('X\u8f74\u6807\u7b7e')<\/p>\n
      plt.ylabel('Y\u8f74\u6807\u7b7e')<\/p>\n
      plt.title('\u67f1\u72b6\u56fe\u6807\u9898')<\/p>\n
      plt.show()<\/p>\n
      <\/code><\/pre>\n<\/p>\n
        \n
      1. \u6563\u70b9\u56fe\uff08Scatter Plot\uff09<\/strong><\/li>\n<\/ol>\n
        \u6563\u70b9\u56fe\u9002\u7528\u4e8e\u663e\u793a\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Matplotlib\u7684scatter<\/code>\u65b9\u6cd5\u6765\u521b\u5efa\u6563\u70b9\u56fe\u3002<\/p>\n<\/p>\n
        plt.figure(figsize=(10, 6))<\/p>\n
        plt.scatter(df_filtered['column1'], df_filtered['column2'])<\/p>\n
        plt.xlabel('X\u8f74\u6807\u7b7e')<\/p>\n
        plt.ylabel('Y\u8f74\u6807\u7b7e')<\/p>\n
        plt.title('\u6563\u70b9\u56fe\u6807\u9898')<\/p>\n
        plt.show()<\/p>\n
        <\/code><\/pre>\n<\/p>\n
        Seaborn\u63d0\u4f9b\u4e86\u521b\u5efa\u6563\u70b9\u56fe\u7684\u9ad8\u7ea7\u63a5\u53e3\uff1a<\/p>\n<\/p>\n
        plt.figure(figsize=(10, 6))<\/p>\n
        sns.scatterplot(x='column1', y='column2', data=df_filtered)<\/p>\n
        plt.xlabel('X\u8f74\u6807\u7b7e')<\/p>\n
        plt.ylabel('Y\u8f74\u6807\u7b7e')<\/p>\n
        plt.title('\u6563\u70b9\u56fe\u6807\u9898')<\/p>\n
        plt.show()<\/p>\n
        <\/code><\/pre>\n<\/p>\n
          \n
        1. \u76f4\u65b9\u56fe\uff08Histogram\uff09<\/strong><\/li>\n<\/ol>\n
          \u76f4\u65b9\u56fe\u9002\u7528\u4e8e\u663e\u793a\u6570\u636e\u7684\u5206\u5e03\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Matplotlib\u7684hist<\/code>\u65b9\u6cd5\u6765\u521b\u5efa\u76f4\u65b9\u56fe\u3002<\/p>\n<\/p>\n
          plt.figure(figsize=(10, 6))<\/p>\n
          plt.hist(df_filtered['column1'], bins=30)<\/p>\n
          plt.xlabel('X\u8f74\u6807\u7b7e')<\/p>\n
          plt.ylabel('Y\u8f74\u6807\u7b7e')<\/p>\n
          plt.title('\u76f4\u65b9\u56fe\u6807\u9898')<\/p>\n
          plt.show()<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          Seaborn\u63d0\u4f9b\u4e86\u521b\u5efa\u76f4\u65b9\u56fe\u7684\u9ad8\u7ea7\u63a5\u53e3\uff1a<\/p>\n<\/p>\n
          plt.figure(figsize=(10, 6))<\/p>\n
          sns.histplot(df_filtered['column1'], bins=30)<\/p>\n
          plt.xlabel('X\u8f74\u6807\u7b7e')<\/p>\n
          plt.ylabel('Y\u8f74\u6807\u7b7e')<\/p>\n
          plt.title('\u76f4\u65b9\u56fe\u6807\u9898')<\/p>\n
          plt.show()<\/p>\n
          <\/code><\/pre>\n<\/p>\n
            \n
          1. \u7bb1\u7ebf\u56fe\uff08Box Plot\uff09<\/strong><\/li>\n<\/ol>\n
            \u7bb1\u7ebf\u56fe\u9002\u7528\u4e8e\u663e\u793a\u6570\u636e\u7684\u5206\u5e03\u53ca\u5176\u5f02\u5e38\u503c\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Seaborn\u7684boxplot<\/code>\u65b9\u6cd5\u6765\u521b\u5efa\u7bb1\u7ebf\u56fe\u3002<\/p>\n<\/p>\n
            plt.figure(figsize=(10, 6))<\/p>\n
            sns.boxplot(x='column1', y='column2', data=df_filtered)<\/p>\n
            plt.xlabel('X\u8f74\u6807\u7b7e')<\/p>\n
            plt.ylabel('Y\u8f74\u6807\u7b7e')<\/p>\n
            plt.title('\u7bb1\u7ebf\u56fe\u6807\u9898')<\/p>\n
            plt.show()<\/p>\n
            <\/code><\/pre>\n<\/p>\n
              \n
            1. \u70ed\u529b\u56fe\uff08Heatmap\uff09<\/strong><\/li>\n<\/ol>\n
              \u70ed\u529b\u56fe\u9002\u7528\u4e8e\u663e\u793a\u77e9\u9635\u6570\u636e\u7684\u503c\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Seaborn\u7684heatmap<\/code>\u65b9\u6cd5\u6765\u521b\u5efa\u70ed\u529b\u56fe\u3002<\/p>\n<\/p>\n
              plt.figure(figsize=(10, 6))<\/p>\n
              sns.heatmap(df_filtered.corr(), annot=True, cmap='coolwarm')<\/p>\n
              plt.title('\u70ed\u529b\u56fe\u6807\u9898')<\/p>\n
              plt.show()<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u4e94\u3001\u603b\u7ed3<\/p>\n<\/p>\n
              \u901a\u8fc7\u5bfc\u5165\u5fc5\u8981\u7684\u5e93\u3001\u8bfb\u53d6\u548c\u7b5b\u9009\u6570\u636e\u3001\u8fdb\u884c\u6570\u636e\u5206\u6790\u3001\u521b\u5efa\u53ef\u89c6\u5316\u56fe\u8868\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Python\u8fdb\u884c\u6570\u636e\u7b5b\u9009\u548c\u7ed8\u56fe\u3002Pandas\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\uff0cMatplotlib\u548cSeaborn\u5219\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u53ef\u89c6\u5316\u5de5\u5177\u3002\u9009\u62e9\u9002\u5408\u7684\u6570\u636e\u7b5b\u9009\u65b9\u6cd5\u548c\u56fe\u8868\u7c7b\u578b\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u66f4\u597d\u5730\u7406\u89e3\u6570\u636e\uff0c\u4ece\u800c\u505a\u51fa\u660e\u667a\u7684\u51b3\u7b56\u3002<\/strong><\/p>\n<\/p>\n
              \u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u4e0d\u540c\u7684\u7b5b\u9009\u548c\u7ed8\u56fe\u65b9\u6cd5\u3002\u4f8b\u5982\uff0c\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u7684\u9ad8\u6548\u6570\u636e\u64cd\u4f5c\u65b9\u6cd5\uff1b\u5728\u521b\u5efa\u590d\u6742\u56fe\u8868\u65f6\uff0c\u53ef\u4ee5\u5229\u7528Seaborn\u7684\u9ad8\u7ea7\u63a5\u53e3\u3002\u5e0c\u671b\u672c\u6587\u5bf9\u60a8\u5728Python\u4e2d\u8fdb\u884c\u6570\u636e\u7b5b\u9009\u548c\u7ed8\u56fe\u6709\u6240\u5e2e\u52a9\u3002<\/p>\n<\/p>\n
              \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
               \u5982\u4f55\u4f7f\u7528Python\u8fdb\u884c\u6570\u636e\u7b5b\u9009\u4ee5\u4fbf\u66f4\u597d\u5730\u53ef\u89c6\u5316\uff1f<\/strong>
              \u5728Python\u4e2d\uff0c\u6570\u636e\u7b5b\u9009\u901a\u5e38\u901a\u8fc7Pandas\u5e93\u5b9e\u73b0\u3002\u53ef\u4ee5\u4f7f\u7528DataFrame<\/code>\u5bf9\u8c61\u7684\u6761\u4ef6\u8fc7\u6ee4\u529f\u80fd\u6765\u9009\u62e9\u7279\u5b9a\u7684\u6570\u636e\u5b50\u96c6\u3002\u6bd4\u5982\uff0c\u60a8\u53ef\u4ee5\u6839\u636e\u67d0\u4e9b\u5217\u7684\u503c\u8fdb\u884c\u7b5b\u9009\uff0c\u63a5\u7740\u4f7f\u7528Matplotlib\u6216Seaborn\u7b49\u5e93\u8fdb\u884c\u53ef\u89c6\u5316\u3002\u5177\u4f53\u6b65\u9aa4\u5305\u62ec\u52a0\u8f7d\u6570\u636e\u3001\u5e94\u7528\u7b5b\u9009\u6761\u4ef6\u3001\u4ee5\u53ca\u7ed8\u5236\u56fe\u8868\u3002<\/p>\n
              Python\u4e2d\u6709\u54ea\u4e9b\u5e38\u7528\u7684\u53ef\u89c6\u5316\u5e93\u53ef\u4ee5\u4e0e\u6570\u636e\u7b5b\u9009\u7ed3\u5408\u4f7f\u7528\uff1f<\/strong>
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