learningcoder的专栏

# -*- coding:utf-8 -*- import pandas as pd # 一行转多行 df = pd.DataFrame( {'Code': ['1111', '2222'], 'Color': ['a, b, c,d', 'blue, pink, yellow'], 'Size': ['1, 2, 3', '7, 6, 10']} ) id_df ...

df1 df2 join是按照行索引来关联操作,列名不能相同 df1.join(df2) #返回df1的行数，df1和df2的所有列名 值没有的话用NaN merge是按照列索引来关联操作，和关系型数据库很相近 1. df1.merge(df2,on=0) #等价于df1.0=df2.0 0 1_x 2 3 4 1_y 0 18 15 19...

# -*- coding:utf-8 -*- import pandas as pd import numpy as np # DataFrame初始化 numpy.ndarray df = pd.DataFrame(np.arange(12).reshape(3, 4), columns=["col" + str(i) for i in range(4)], index=list("ABC"...

# -*- coding:utf-8 -*- import pandas as pd import string ''' Series 对象是由两个数组组成，一个是索引(Index) 一个是值(values) 构造成键值对 ''' # Series数据初始化 列表 s1 = pd.Series([1, 2, 3], index=["a", "b", "c"]) print(type(s1))...