replace NAN or blank with string pandas dataframe

Question

I have a pandas data frame. In one of the columns ('Q8') of this data frame, some of the rows are empty. I would like to replace these empty cells with a string ('ss'). I want to do this replacement with a condition. This condition is that if the string in column ('Q7') is ('I am a student') and the cell in this row at column ('Q8') is empty, replace the empty cell of column ('Q8') with 'ss'.

This is the code which I wrote for it:

for xx in range(0,len(df['Q8'])):
    if df['Q8'][xx]==np.nan:
       if df['Q7'][xx]=='I am a student':
           df['Q8'][xx].replace('', 'ss', regex=True)

but it can not find any np.nan from the first if!!

gmds · Accepted Answer · 2019-03-07 01:45:29Z

4

Use masking instead:

df.loc[(df['Q7'] == 'I am a student') & (df['Q8'].isna()), 'Q8'] = 'ss'

You can also use fillna:

df.loc[df['Q7'] == 'I am a student', 'Q8'] = df.loc[df['Q7'] == 'I am a student', 'Q8'].fillna('ss')

edited Mar 7, 2019 at 1:45

answered Mar 7, 2019 at 1:36

gmds

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4 Comments

AlexK Over a year ago

@CFD and note the use of the isna() function for finding missing values, which works across different data types.

CFD Over a year ago

Why should we put 'Q8' at the end of first method?

gmds Over a year ago

@CFD because we need to mask in two dimensions: we want to modify only the cells which belong to rows where df[Q7] has the value 'I am a student' and columns where df[Q8] is null.

AlexK Over a year ago

@CFD also, the proper syntax for using the .loc indexer is: df.loc[row_indexer,column_indexer].

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