Filling null values within a Pandas DataFrame with values from the same column that have a matching value in another column

Question

I have a DataFrame that has nulls within a given column, within the same index, there is another column with repeating non Null values. What I am trying to figure out is what's the proper way of filling those null values using the ID column as reference using Pandas native functions.

Thank you for your help.

Original:

    Company ID
    AAA 100
    BBB 200
    CCC 150
    **NULL  100
    FFF 375
    **NULL  150

Formatted:

    AAA 100
    BBB 200
    CCC 150
    **AAA   100
    FFF 375
    **CCC   150

Answer 1

You can try:

df['Company'] = df.groupby('ID')['Company'].transform('first')

---

As commented, the above will replace all Company not just those with nan. So it may give wrong result if you have several Company for an ID. Instead, you can do:

df['Company'] = df['Company'].fillna(df.groupby('ID')['Company'].transform('first'))