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()
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With