Union all of two data frames in pandas can be easily achieved by using concat() function. Lets see with an example. First lets create two data frames
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import pandas as pdimport numpy as np#Create a DataFramedf1 = { ‘Subject‘:[‘semester1‘,‘semester2‘,‘semester3‘,‘semester4‘,‘semester1‘, ‘semester2‘,‘semester3‘], ‘Score‘:[62,47,55,74,31,77,85]}df2 = { ‘Subject‘:[‘semester1‘,‘semester2‘,‘semester3‘,‘semester4‘], ‘Score‘:[90,47,85,74]}df1 = pd.DataFrame(df1,columns=[‘Subject‘,‘Score‘])df2 = pd.DataFrame(df2,columns=[‘Subject‘,‘Score‘])df1df2 |
UNION ALL
concat() function in pandas creates the union of two dataframe.
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""" Union all in pandas"""df_union_all= pd.concat([df1, df2])df_union_all |
union all of two dataframes df1 and df2 is created with duplicates. So the resultant dataframe will be
concat() function in pandas creates the union of two dataframe with ignore_index = True will reindex the dataframe
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""" Union all with reindex in pandas"""df_union_all= pd.concat([df1, df2],ignore_index=True)df_union_all |
union all of two dataframes df1 and df2 is created with duplicates and the index is changed. So the resultant dataframe will be
UNION
ref:http://www.datasciencemadesimple.com/union-and-union-all-in-pandas-dataframe-in-python-2/
Python union，union 2个dataset数据
原文：https://www.cnblogs.com/watermarks/p/13153910.html