访问每一行并检查数据框中的每一列值

Question

I want to iterate over each row and and want to check in each column if value is NaN if it is then i want to replace it with the previous value of the same row which is not null.

I believe the prefer way would be using lamba function. But still not figure out to code it Note: I have thousands of rows and 200 columns in each row

Answer 1

The following should do the work:

df.fillna(method='ffill', axis=1, inplace=True)

Can you please clarify what you want to be done with NaNs in first column(s)?

Answer 2

我想你可以用这个 -

your_df.apply(lambda x : x.fillna(method='ffill'), axis=1)