zoukankan      html  css  js  c++  java
  • pandas之透视表和交叉表

    import pandas as pd
    import warnings
    
    warnings.filterwarnings('ignore')
    
    # 读取用户表
    users = pd.read_table('./users.dat', header=None, names=['UserID', 'Gender', 'Age', 'Occupation', 'Zip-code'], sep='::',
                          engine='python')
    # print(users.head())
    # 读取评分表
    ratings = pd.read_table('./ratings.dat', header=None, names=['UserID', 'MovieID', 'Rating', 'Timestamp'], sep='::',
                            engine='python')
    # print(ratings.head())
    # 读取电影详情表
    movies = pd.read_table('./movies.dat', header=None, names=['MovieID', 'Title', 'Genres'], sep='::', engine='python')
    # print(movies.head())
    # 将表进行合并
    data = pd.merge(pd.merge(ratings, users), movies)
    print(data.head())
    
    # 使用pivot_table方法查看,每一部电影不同性别的平均评分
    data_gender = pd.pivot_table(data, index='Title', columns='Gender', values='Rating', margins=True)
    # data_gender = data.pivot_table(index='Title', columns='Gender', values='Rating')
    print(data_gender.head())
    
    # 使用groupby方法
    data_gender = data.groupby(['Title', 'Gender']).agg({'Rating': 'mean'})
    print(data_gender.head())
    
    # 使用crosstab方法查看每一部电影不同性别的平均评分
    data_gender = pd.crosstab(data.Title, data.Gender, data.Rating, aggfunc='mean')
    print(data_gender.head())
    
    
    输出结果:
       UserID  MovieID  ...                                   Title  Genres
    0       1     1193  ...  One Flew Over the Cuckoo's Nest (1975)   Drama
    1       2     1193  ...  One Flew Over the Cuckoo's Nest (1975)   Drama
    2      12     1193  ...  One Flew Over the Cuckoo's Nest (1975)   Drama
    3      15     1193  ...  One Flew Over the Cuckoo's Nest (1975)   Drama
    4      17     1193  ...  One Flew Over the Cuckoo's Nest (1975)   Drama
    
    [5 rows x 10 columns]
    Gender                                F         M       All
    Title                                                      
    $1,000,000 Duck (1971)         3.375000  2.761905  3.027027
    'Night Mother (1986)           3.388889  3.352941  3.371429
    'Til There Was You (1997)      2.675676  2.733333  2.692308
    'burbs, The (1989)             2.793478  2.962085  2.910891
    ...And Justice for All (1979)  3.828571  3.689024  3.713568
                                        Rating
    Title                     Gender          
    $1,000,000 Duck (1971)    F       3.375000
                              M       2.761905
    'Night Mother (1986)      F       3.388889
                              M       3.352941
    'Til There Was You (1997) F       2.675676
    Gender                                F         M
    Title                                            
    $1,000,000 Duck (1971)         3.375000  2.761905
    'Night Mother (1986)           3.388889  3.352941
    'Til There Was You (1997)      2.675676  2.733333
    'burbs, The (1989)             2.793478  2.962085
    ...And Justice for All (1979)  3.828571  3.689024
    import pandas as pd
    
    data = pd.DataFrame({'Sample': range(1, 11),
                         'Gender': ['Female', 'Male', 'Female', 'Male', 'Male', 'Male', 'Female', 'Female', 'Male',
                                    'Female'],
                         'Handedness': ['Right-handed', 'Left-handed', 'Right-handed', 'Right-handed', 'Left-handed',
                                        'Right-handed', 'Right-handed', 'Left-handed', 'Right-handed', 'Right-handed']})
    print(data)
    
    # 方法1 :使用pivot_table
    data1 = pd.pivot_table(data, index='Gender', columns='Handedness', aggfunc=len, margins=True)
    print(data1)
    
    # 方法2:使用crosstab
    data2 = pd.crosstab(data.Gender, data.Handedness, data.Sample, aggfunc=len, margins=True)
    print(data2)
    
    输出结果:
       Sample  Gender    Handedness
    0       1  Female  Right-handed
    1       2    Male   Left-handed
    2       3  Female  Right-handed
    3       4    Male  Right-handed
    4       5    Male   Left-handed
    5       6    Male  Right-handed
    6       7  Female  Right-handed
    7       8  Female   Left-handed
    8       9    Male  Right-handed
    9      10  Female  Right-handed
                    Sample                 
    Handedness Left-handed Right-handed All
    Gender                                 
    Female               1            4   5
    Male                 2            3   5
    All                  3            7  10
    Handedness  Left-handed  Right-handed  All
    Gender                                    
    Female                1             4    5
    Male                  2             3    5
    All                   3             7   10
  • 相关阅读:
    intellij idea 主题更换(换黑底或白底)
    intellij idea 编码设置(乱码问题)
    Intellij idea中maven加载jar包很慢的解决方案.
    mysql一个特殊的条件.字符串除以0的结果.
    tomcat启动报错:Injection of autowired dependencies failed
    给input文本框添加灰色提示文字,三种方法.
    jquery插件开发尝试(二)
    初试jquery插件开发
    jquery.touchslider.min.js的简单使用
    superslide 学习笔记
  • 原文地址:https://www.cnblogs.com/yuxiangyang/p/11266863.html
Copyright © 2011-2022 走看看