Pandas教程-数据连接

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))  

输出:

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

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]))  

输出:

    Name     id
A   Parker   108
B   Phill    119
C   Smith    127
A   Terry    102
B   Jones    125
C   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']))  

输出:

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