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