pandas库中concat()、merge()、groupby()、pivot_table()相关用法-优快云博客

本文链接：https://blog.youkuaiyun.com/zhangmary/article/details/79641465

本文通过示例介绍了Python pandas库中的关键函数，包括concat()用于拼接数据帧，merge()进行数据合并，groupby()对数据进行分组聚合，以及pivot_table()生成数据透视表。详细展示了这些函数的用法和效果，帮助读者深入理解pandas的数据处理能力。

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#!/usr/bin/env python
# -*- coding:utf-8 -*-
import pandas as pd
import numpy as np
import datetime

def main():
    dates = pd.date_range("20180301", periods=8)
    df = pd.DataFrame(np.random.randn(8, 5), index=dates, columns=list('ABCDE'))  # randn正态分布中随机数#
    print (df)
    #concat#
    pieces =[df[:3],df[-3:]]
    print (pd.concat(pieces))
    left=pd.DataFrame({"key":["x","y"],"value":[1,2]})
    right=pd.DataFrame({"key":["y","z"],"value":[4,5]})
    print ("LEFT:",left)
    print ("RIGHT:",right)
    print (pd.merge(left, right, on="key", how ="outer"))#合并#
    df2 = pd.DataFrame({"A":["a","b","c","b"],"B":list(range(4))})
    print (df2.groupby("A").sum())#将相同索引的值进行合并#
    #reshape# 制作透视表
    df3 = pd.DataFrame({'A':['one','one','two','three']*6,
                        'B':['a','b','c']*8,
                        'C':['foo','foo','foo','bar','bar','bar']*4,
                        'D':np.random.randn(24),
                        'E':np.random.randn(24),
                        'F':[datetime.datetime(2018,i,1)for i in range(1,13)]+
                            [datetime.datetime(2018,i,15)for i in range(1,13)]})
    print (pd.pivot_table(df3, values="D", index=["A","F"],columns=["C"] )) #输出数据透视表#

if __name__ == "__main__":
     main()