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I have two dataframes DF1, DF2 which have the same type of data and share some index values but not all
DF1
index, a, b, c
[ abc 1, 3, 6 ]
[ acb 2, 4, 5 ]
[ cab 6, 5, 2 ]
[ bac 3, 6, 2 ]
[ bca 6, 8, 3 ]
DF2
index, a, b, d
[ abc 4, 7, 3 ]
[ kde 2, 5, 8 ]
[ lat 7, 2, 6 ]
[ bac 0, 4, 4 ]
[ bca 3, 6, 8 ]
as a result I want to achieve the following
1.) Add column D to DF1 based on the index match
2.) Add index and rows from DF2which are not present in DF1
RESULT
index, a, b, c, d
[ abc 1, 3, 6, 3 ]
[ acb 2, 4, 5, - ]
[ cab 6, 5, 2, - ]
[ bac 3, 6, 2, 4 ]
[ bca 6, 8, 3, 8 ]
[ kde 2, 5, -, 8 ]
[ lat 7, 2, -, 6 ]
505
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How to update the value of a row in a Python Dataframe? 1. Using Python at () method to update the value of a row. Python at () method enables us to update the value of one row... 2. Python loc () function to change the value of a row/column. Python loc () method can also be used to update the ...
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Let use combine_first:
Create data:
DF1 = pd.DataFrame({'a':[1,2,6,3,6],'b':[3,4,5,6,8],'c':[6,5,2,2,3]},index=['abc','acb','cab','bac','bca'])
DF2 = pd.DataFrame({'a':[4,2,7,0,3],'b':[7,5,2,4,6],'d':[3,8,6,4,8]},index=['abc','kde','lat','bac','bca'])
df_combo = DF1.combine_first(DF2)
print(df_combo)
a b c d
abc 1.0 3.0 6.0 3.0
acb 2.0 4.0 5.0 NaN
bac 3.0 6.0 2.0 4.0
bca 6.0 8.0 3.0 8.0
cab 6.0 5.0 2.0 NaN
kde 2.0 5.0 NaN 8.0
lat 7.0 2.0 NaN 6.0
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