series1=pd.Series([1,2,3],name=‘s1‘) series2=pd.Series([4,5,6],name=‘s2‘) df = pd.concat([series1, series2], axis=1)
Out:
series1=pd.Series([1,2,3],index=[‘a‘,‘b‘,‘c‘],name=‘s1‘) series2=pd.Series([4,5,6],index=[‘a‘,‘b‘,‘d‘],name=‘s2‘) df = pd.concat([series1, series2], axis=1)
Out:
Note: Two series must have names.
df=pd.DataFrame([1,2,3],index=[‘a‘,‘b‘,‘c‘],columns=[‘s1‘]) s2=pd.Series([4,5,6],index=[‘a‘,‘b‘,‘d‘],name=‘s2‘) df[‘s2‘]=s2
Out:
This method is equivalant to left join:
d2.join(s2,how=‘left‘,inplace=True)
To get the same result as Part 1, we can use outer join:
d2.join(s2,how=‘outer‘,inplace=True)
[Python Cookbook]Pandas: How to increase columns for DataFrame?Join/Concat
原文：https://www.cnblogs.com/sherrydatascience/p/12375589.html