I have following tables in a pandas dataframe:

My aim is a table of form:

What is the easiest way to do that with python?

CodePudding user response：

Perform multiple merges in a chain:

df1.merge(df2.merge(df3))

#      ID1    ID2  Value1  Value2  Value3
# 0  Data1  Data2  Data11  Data12  Data13

Or with functools.reduce syntax:

from functools import reduce
reduce(lambda L, R: L.merge(R, on=['ID1', 'ID2']), [df1, df2, df3])

CodePudding user response：

new_df = pd.concat([df1, df2, df3]).groupby(['ID1', 'ID2'], as_index=False).first()

Output:

>>> new_df
     ID1    ID2  Value1  Value2  Value3
0  Data1  Data2  Data11  Data12  Data13

CodePudding user response：

It's very similar to @user17242583's answer. The only difference is, nth(0) will get the first even if it's NaN while first won't.

df_new = pd.concat([df1, df2, df3]).groupby(['ID1', 'ID2'], as_index=False).nth(0)