I'm trying to fill a column of a dataframe from another dataframe based on conditions. Let's say my first dataframe is df1 and the second is named df2.
# df1 is described as bellow :
+------+------+
| Col1 | Col2 |
+------+------+
|   A  |  1   |
|   B  |  2   |
|   C  |  3   |
|   A  |  1   |
+------+------+
And
# df2 is described as bellow :
+------+------+
| Col1 | Col2 |
+------+------+
|   A  |  NaN |
|   B  |  NaN |
|   D  |  NaN |
+------+------+
Each distinct value of Col1 has her an id number (In Col2), so what I want is to fill the NaN values in df2.Col2 where df2.Col1==df1.Col1 . So that my second dataframe will look like :
# df2 :
+------+------+
| Col1 | Col2 |
+------+------+
|   A  |  1   |
|   B  |  2   |
|   D  |  NaN |
+------+------+
I'm using Python 2.7
Use drop_duplicates with set_index and combine_first:
df = df2.set_index('Col1').combine_first(df1.drop_duplicates().set_index('Col1')).reset_index()
If need check dupes only in id column:
df = df2.set_index('Col1').combine_first(df1.drop_duplicates().set_index('Col1')).reset_index()
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