创建dateframe数据结构，并完成以下操作任务，详细题目如图所示。

灰太狼 2022-12-29 11:23 34阅读 0赞

## 创建dateframe数据结构，并完成以下操作任务，详细题目如下图所示： ##

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import pandas as pd
    
    df = pd.DataFrame({
        "xuehao": ['20180101001', '20180101002', '20180101003', '20180101004', '20180101005', '20180101006',
                                  '20180101007', '20180101008', '20180101009', '20180101010'],
                       "xingming": ['liuyang', 'chenxi', 'zhangli', 'liming', 'wangcheng', 'wuyue', 'sunqiang', 'zhaoqi',
                                    'wuqing', 'xiyue'],
                       "xingbie": ['Female', 'Man', 'Man', 'Female', 'Female', 'Man', 'Man', 'Female', 'Female', 'Man'],
                       "yingyu": [88, 85, 92, 76, 90, 46, 82, 96, 36, 68],
                       "jisuanji": [90, 85, 79, 98, 76, 82, 86, 63, 80, 53],
                       "shuxue": [78, 90, 82, 88, 93, 72, 85, 99, 95, 69]},
                      columns=["xuehao", "xingming", "xingbie", "yingyu", "jisuanji", "shuxue"])
    print(df)
    print("前五行的数据信息为：\n", df.head())
    print("后五行的数据信息为：\n", df.tail())
    print("df行和列的索引值为：", df.index, df.columns.tolist())
    print("xingming列的值为：\n", df["xingming"])
    print("yingyu列的值为：\n", df["yingyu"])
    print("jisuanji列的值为：\n", df["jisuanji"])
    print("shuxue列的值为：\n", df["shuxue"])
    print("切片2~6行为：\n", df.iloc[1:6])
    print("切片1~5列为：\n", df.iloc[:, 0:5])
    print("第2~8行的第1，3，4，5列的所有数据为：\n", df.iloc[1:8, [0, 2, 3, 4]])
    print("筛选出xingbie列值为Female的所有数据：\n", df.loc[df['xingbie'].isin(['Female'])])
    print("筛选出xingbie列值为非Female的所有数据：\n", df.loc[df['xingbie'].isin(['Man'])])
    print("按xingbie分组，求出yingyu的平均分：\n", df.groupby('xingbie')['yingyu'].mean())
    print("按xingbie分组，求出jisuanji的平均分：\n", df.groupby('xingbie')['jisuanji'].mean())
    print("按xingbie分组，求出shuxue的平均分：\n", df.groupby('xingbie')['shuxue'].mean())
    df['gender_n'] = df.xingbie.apply(lambda x: 1 if 'Man' in x else 0)
    print("添加gender_n到最后一列，男性填1，女性填0：\n", df)
    print("获取男性和女性的yingyu、jisuanji、shuxue的最高分和最低分：\n最高分：\n", df.iloc[:, 3:6].max(), "\n最低分：\n", df.iloc[:, 3:6].min())
    print("yingyu男女的最高分和最低分：\n", df.groupby('xingbie').yingyu.agg(['max', 'min']))
    print("jisuanji男女的最高分和最低分：\n", df.groupby('xingbie').jisuanji.agg(['max', 'min']))
    print("shuxue男女的最高分和最低分：\n", df.groupby('xingbie').shuxue.agg(['max', 'min']))
    print("删除最后一列gender_n：\n", df.drop(['gender_n'], axis=1, inplace=True))
    df['xingming'] = df['xingming'].map(lambda x: x.capitalize())
    print("将xingming列中所有数据首字母大写：\n", df)
    print("将xuehao列总分设置为行索引：\n", df.set_index(["xuehao"]))
    df['score_sun'] = df.iloc[:, 3:6].sum(axis=1)
    print("在最后添加一列score_sun，计算每位学生各科的总分，并按总分从大到小的顺序排序：\n", df.sort_values(by=['score_sun'], ascending=False))

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![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl81MjE4NDgxNQ_size_16_color_FFFFFF_t_70 4]

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