📜  Pandas 数据concat

📅  最后修改于: 2020-10-29 05:23:04             🧑  作者: Mango

串联数据

NumPy的连接数据用于连接两个数组,行或列。它可以采用两个或多个相同形状的数组,并且按行串联作为默认类型,即axis = 0。

范例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]])

范例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

范例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