I’m trying to merge two dataframes in Pandas based on a common column, ID. After merging, I want to update a column, Target Value, in my original dataframe (df) using a column from the second dataframe (reference). However, not all rows are being updated as expected, even though the ID values are exact match.
For example, it would update only 4 out of 10 rows I have in my dataframe.

I’m trying to merge two dataframes in Pandas based on a common column, ID. After merging, I want to update a column, Target Value, in my original dataframe (df) using a column from the second dataframe (reference). However, not all rows are being updated as expected, even though the ID values are exact match.
For example, it would update only 4 out of 10 rows I have in my dataframe.

I’m trying to merge two dataframes in Pandas based on a common column, ID. After merging, I want to update a column, Target Value, in my original dataframe (df) using a column from the second dataframe (reference). However, not all rows are being updated as expected, even though the ID values are exact match.
For example, it would update only 4 out of 10 rows I have in my dataframe.

I’m trying to merge two dataframes in Pandas based on a common column, ID. After merging, I want to update a column, Target Value, in my original dataframe (df) using a column from the second dataframe (reference). However, not all rows are being updated as expected, even though the ID values are exact match.
For example, it would update only 4 out of 10 rows I have in my dataframe.

I’m trying to merge two dataframes in Pandas based on a common column, ID. After merging, I want to update a column, Target Value, in my original dataframe (df) using a column from the second dataframe (reference). However, not all rows are being updated as expected, even though the ID values are exact match.
For example, it would update only 4 out of 10 rows I have in my dataframe.

So basically I’m merging 2 very large dataframes on a column with an inner join using the .merge() method. I’ve seen people suggest to remove blank values from the column, however there are none, and blanks elsewhere are vital for the analysis of the data.