I have this type of DataFrame
name surname middle
Frank Doe NaN
John Nan Wood
Jack Putt Nan
Frank Nan Joyce
I want to move "middle" values on NaN same rows values on "surname" column. How can i do this? I tried to use the fillna method but got no results. Here is my code:
import os
from pandas.io.parsers import read_csv
for csvFilename in os.listdir('.'):
if not csvFilename.endswith('.csv'):
continue
data=read_csv(csvFilename)
filtered_data["surname"].fillna(filtered_data["middle"].mean(),inplace=True)
filtered_data.to_csv('output.csv' , index=False)
Using pd.isnull(), columns can be rearranged conditionally.
import pandas as pd
from cStringIO import StringIO
# Create fake DataFrame... you can read this in however you like
df = pd.read_table(StringIO('''
name surname middle
Frank Doe NaN
John NaN Wood
Jack Putt NaN
Frank NaN Joyce'''), sep='\s+')
print 'Original DataFrame:'
print df
print
# Assign the middle name to any surname with a NaN
df.loc[pd.isnull(df['surname']), 'surname'] = df[pd.isnull(df['surname'])]['middle']
print 'Manipulated DataFrame:'
print df
print
Original DataFrame:
name surname middle
0 Frank Doe NaN
1 John NaN Wood
2 Jack Putt NaN
3 Frank NaN Joyce
Manipulated DataFrame:
name surname middle
0 Frank Doe NaN
1 John Wood Wood
2 Jack Putt NaN
3 Frank Joyce Joyce
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