concat可以实现横向或纵向合并多个DataFrame
import pandas as pd
import numpy as np
# concatenating
df1 = pd.DataFrame(np.ones((3,4))*0,columns = ['a','b','c','d'])
df2 = pd.DataFrame(np.ones((3,4))*1,columns = ['a','b','c','d'])
df3 = pd.DataFrame(np.ones((3,4))*2,columns = ['a','b','c','d'])
print(df1)
print(df2)
print(df3)
a b c d
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
a b c d
0 1.0 1.0 1.0 1.0
1 1.0 1.0 1.0 1.0
2 1.0 1.0 1.0 1.0
a b c d
0 2.0 2.0 2.0 2.0
1 2.0 2.0 2.0 2.0
2 2.0 2.0 2.0 2.0
concat：上下合并axis=0 左右合并axis=1
res = pd.concat([df1,df2,df3],axis=0)
print(res)
a b c d
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
0 1.0 1.0 1.0 1.0
1 1.0 1.0 1.0 1.0
2 1.0 1.0 1.0 1.0
0 2.0 2.0 2.0 2.0
1 2.0 2.0 2.0 2.0
2 2.0 2.0 2.0 2.0
ignore_index = True 忽略原index，重新排序
res = pd.concat([df1,df2,df3],axis=0,ignore_index = True)
print(res)
a b c d
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
3 1.0 1.0 1.0 1.0
4 1.0 1.0 1.0 1.0
5 1.0 1.0 1.0 1.0
6 2.0 2.0 2.0 2.0
7 2.0 2.0 2.0 2.0
8 2.0 2.0 2.0 2.0
join：['inner','outer']
df1 = pd.DataFrame(np.ones((3,4))*0,columns = ['a','b','c','d'],index = [1,2,3])
df2 = pd.DataFrame(np.ones((3,4))*1,columns = ['b','c','d','e'],index = [2,3,4])
print(df1)
print(df2)
a b c d
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
3 0.0 0.0 0.0 0.0
b c d e
2 1.0 1.0 1.0 1.0
3 1.0 1.0 1.0 1.0
4 1.0 1.0 1.0 1.0
默认join='outer' 取并集
res = pd.concat([df1,df2])
print(res)
a b c d e
1 0.0 0.0 0.0 0.0 NaN
2 0.0 0.0 0.0 0.0 NaN
3 0.0 0.0 0.0 0.0 NaN
2 NaN 1.0 1.0 1.0 1.0
3 NaN 1.0 1.0 1.0 1.0
4 NaN 1.0 1.0 1.0 1.0
join='inner' 取交集
res = pd.concat([df1,df2],join='inner')
print(res)
b c d
1 0.0 0.0 0.0
2 0.0 0.0 0.0
3 0.0 0.0 0.0
2 1.0 1.0 1.0
3 1.0 1.0 1.0
4 1.0 1.0 1.0
join_axes
默认取并集
res = pd.concat([df1,df2],axis=1)
print(res)
a b c d b c d e
1 0.0 0.0 0.0 0.0 NaN NaN NaN NaN
2 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0
3 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0
4 NaN NaN NaN NaN 1.0 1.0 1.0 1.0
按df1的index合并
res = pd.concat([df1,df2],axis=1,join_axes=[df1.index])
print(res)
a b c d b c d e
1 0.0 0.0 0.0 0.0 NaN NaN NaN NaN
2 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0
3 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0
append 默认上下合并
df1 = pd.DataFrame(np.ones((3,4))*0,columns = ['a','b','c','d'])
df2 = pd.DataFrame(np.ones((3,4))*1,columns = ['a','b','c','d'])
df3 = pd.DataFrame(np.ones((3,4))*1,columns = ['a','b','c','d'])
res = df1.append(df2,ignore_index = True)
print(res)
a b c d
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
3 1.0 1.0 1.0 1.0
4 1.0 1.0 1.0 1.0
5 1.0 1.0 1.0 1.0
添加多个DataFrame
res = df1.append([df2,df3],ignore_index = True)
print(res)
a b c d
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
3 1.0 1.0 1.0 1.0
4 1.0 1.0 1.0 1.0
5 1.0 1.0 1.0 1.0
6 1.0 1.0 1.0 1.0
7 1.0 1.0 1.0 1.0
8 1.0 1.0 1.0 1.0
DateFrame添加Series
df1 = pd.DataFrame(np.ones((3,4))*0,columns = ['a','b','c','d'])
s1 = pd.Series([1,2,3,4],index = ['a','b','c','d']) # 一维矩阵（向量）的index就是column
res = df1.append(s1,ignore_index = True)
print(res)
a b c d
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
3 1.0 2.0 3.0 4.0
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