pandas Python 熊猫：垂直和水平连接
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Python pandas: concat vertical and horizontal
提问by user27074
I am trying to concat two dataframe, horizontally. df2 contains 2 result variables for every observation in df1.
我正在尝试水平连接两个数据框。df2 包含 df1 中每个观察的 2 个结果变量。
df1.shape
(242583, 172)
df2.shape
(242583, 2)
My code is:
我的代码是：
Fin = pd.concat([df1, df2], axis= 1)
But somehow the result is stacked in 2 dimensions:
但不知何故，结果以二维方式堆叠：
Fin.shape
(485166, 174)
What am I missing here?
我在这里错过了什么？
回答by jezrael
There are different index values, so indexes are not aligned and get NaNs:
有不同的索引值，所以索引没有对齐，得到NaNs：
df1 = pd.DataFrame({
'A': ['a','a','a'],
'B': range(3)
})
print (df1)
A B
0 a 0
1 a 1
2 a 2
df2 = pd.DataFrame({
'C': ['b','b','b'],
'D': range(4,7)
}, index=[5,7,8])
print (df2)
C D
5 b 4
7 b 5
8 b 6
Fin = pd.concat([df1, df2], axis= 1)
print (Fin)
A B C D
0 a 0.0 NaN NaN
1 a 1.0 NaN NaN
2 a 2.0 NaN NaN
5 NaN NaN b 4.0
7 NaN NaN b 5.0
8 NaN NaN b 6.0
One possible solution is create default indexes:
一种可能的解决方案是创建默认索引：
Fin = pd.concat([df1.reset_index(drop=True), df2.reset_index(drop=True)], axis= 1)
print (Fin)
A B C D
0 a 0 b 4
1 a 1 b 5
2 a 2 b 6
Or assign:
或赋值：
df2.index = df1.index
Fin = pd.concat([df1, df2], axis= 1)
print (Fin)
A B C D
0 a 0 b 4
1 a 1 b 5
2 a 2 b 6
df1.index = df2.index
Fin = pd.concat([df1, df2], axis= 1)
print (Fin)
A B C D
5 a 0 b 4
7 a 1 b 5
8 a 2 b 6
