Update column values based on another dataframe's index

Question

I have the following dataframes:

NUMS = ['1', '2', '3', '4', '5'] LETTERS = ['a', 'b', 'c'] df1 = pd.DataFrame(index=NUMS, columns=LETTERS) a b c 1 NaN NaN NaN 2 NaN NaN NaN 3 NaN NaN NaN 4 NaN NaN NaN 5 NaN NaN NaN df2 = pd.DataFrame([['tom', 10], ['nick', 15], ['james', 14]], index=LETTERS, columns=['col', 'col2']) col col2 a tom 10 b nick 15 c james 14

I'm trying to update df1 with df2 so that if the column matches the index from df2, all rows are updated with col2:

 a b c 1 10 15 14 2 10 15 14 3 10 15 14 4 10 15 14 5 10 15 14

I've tried df1.update(df2['col2']), but df1 does not update.

I've also tried df1.apply(lambda x: df2['col2'].loc[x]), but I'm getting the following error:

KeyError: "None of [Float64Index([nan, nan, nan, nan, nan], dtype='float64')] are in the [index]"

Thank you!

ziying35 · Accepted Answer · 2022-05-07 00:53:30Z

1

try this:

df1.fillna(df2.col2) >>> a b c 1 10 15 14 2 10 15 14 3 10 15 14 4 10 15 14 5 10 15 14

answered May 7, 2022 at 0:53

ziying35

1,3155 silver badges6 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

Idan Hazan · Accepted Answer · 2022-05-07 00:21:56Z

Try this:

for column in df1.columns: df1.loc[:, column] = df2.at[column, 'col2']

Collectives™ on Stack Overflow

Update column values based on another dataframe's index

2 Answers 2

Comments

Comments

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

Comments

Comments

Related