Pandas 教程-数据连接

整理：python架构师

NumPy的concatenate函数用于沿着行或列连接两个数组。它可以接受两个或更多形状相同的数组，默认按行连接，即axis=0。

示例1:

# import numpy  import numpy as np  arr1 = np.arange(9)  arr1  arr2d_1 = array.reshape((3,3))  arr2d_1      arr2d_1 = np.arange(10,19).reshape(3,3)  arr2d_1  # concatenate 2 numpy arrays: row-wise  np.concatenate((arr2d_1, arr2d_2))

array([[ 0,  1,  2],       [ 3,  4,  5],       [ 6,  7,  8],       [10, 11, 12],       [13, 14, 15],       [16, 17, 18]])

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示例2:

import pandas as pd  one = pd.DataFrame({'Name': ['Parker', 'Phill', 'Smith'],'id':[108,119,127]},index=['A','B','C'])  two = pd.DataFrame({'Name': ['Terry', 'Jones', 'John'],                        'id':[102,125,112]},  index=['A','B','C'])  print(pd.concat([one,two]))

    Name     idA   Parker   108B   Phill    119C   Smith    127A   Terry    102B   Jones    125C   John     112

示例3:

import pandas as pd  one = pd.DataFrame({'Name': ['Parker', 'Phill', 'Smith'],'id':[108,119,127]},index=['A','B','C'])  two = pd.DataFrame({'Name': ['Terry', 'Jones', 'John'],                        'id':[102,125,112]},  index=['A','B','C'])  print(pd.concat([one,two],keys=['x','y']))

 Name   idx A  Parker  108B   Phill119 C   Smith  127y A   Terry  102 B   Jones  125C    John  112

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