CODEWITHSUNDEEP
pythonpandasnumpyjoinmerge
Vishal Anand
Vishal Anand

Reputation: 178

How to fill specific values from one dataframe to another dataframe

I have one bigger dataframe ( A ) and a smaller dataframe ( B ).
A ( larger dataframe )

from   val  null
Abc_1   45  76
Abc_2   46  77
Abc_3   47  78
Abc_4   48  79
Abc_5   49  80
Abc_6   50  81
Abc_7   51  82
Abc_8   52  83
Abc_9   53  84
Abc_10  54  85
.
.
.

B (smaller dataframe)

from    null
Abc_3   3
Abc_8   3
Abc_4   5
Abc_1   2
Abc_6   4
.
.
.

The "from" column is the index of both dataframe. The "from" of B dataframe is subset of "from" of A datframe but it is in jumbled manner ( not in the same order as of A dataframe.)

I want to do some operation which will take the "null" of B datframe of respective rows and replace the "null" of the A dataframe

So the resulting dataframe output should look something like this.

from   val  null
Abc_1   45  2
Abc_2   46  77
Abc_3   47  3
Abc_4   48  5
Abc_5   49  80
Abc_6   50  4
Abc_7   51  82
Abc_8   52  3
Abc_9   53  84
Abc_10  54  85
.
.
.

Upvotes: 2

Views: 226

Answers (1)

jezrael
jezrael

Reputation: 863291

Use Series.map by Series from B by select null column an repalce non matched values by original column by Series.fillna:

A['null'] = A.index.to_series().map(B['null']).fillna(A['null']).astype(int)
print (A)
        val  null
from             
Abc_1    45     2
Abc_2    46    77
Abc_3    47     3
Abc_4    48     5
Abc_5    49    80
Abc_6    50     4
Abc_7    51    82
Abc_8    52     3
Abc_9    53    84
Abc_10   54    85

Or use left join in DataFrame.merge with DataFrame.pop for extract column and Series.fillna:

Notice: This solution is better if need processing multiple columns.

df = A.merge(B, on='from', how='left', suffixes=('','_'))
df['null'] = df.pop('null_').fillna(df['null']).astype(int)
print (df)
        val  null
from             
Abc_1    45     2
Abc_2    46    77
Abc_3    47     3
Abc_4    48     5
Abc_5    49    80
Abc_6    50     4
Abc_7    51    82
Abc_8    52     3
Abc_9    53    84
Abc_10   54    85

Upvotes: 2

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