why is df.fillna() only filling some rows and the first column

Question

Trying to fill all empty spots rows and columns with [], however fillna() will only do some rows and the first column. My code has worked in previous runs so I'm not sure what happened.

    df = df.fillna(value = "[]")
    print(df[['keywords']])
    df.to_csv(r'C:\Users\user\dfexport.csv', index=False, header=True)

When looking at the csv file it looks like:export.csv

The print statement looks like:print(df[['keywords]])

Perhaps some of those cells are empty strings instead of NaN — Henry Ecker, Aug 14 '21 at 15:20

score 0 · Accepted Answer · answered Aug 14 '21 at 15:41

0

import pandas as pd
import numpy as np
 
# initialize list of lists
data = [['tom', 10], ['',''], []]
# Create the pandas DataFrame
df = pd.DataFrame(data, columns = ['Name', 'Age'])
df.replace('', np.nan, inplace=True)
df = df.fillna(value = "[]")
print(df)

answered Aug 14 '21 at 15:41

Nukala Raghava Aditya

45
2

This does work but something odd is going on it will replace with Nan but when printing the data frame instead of having a value of None or Nan it is completely empty nothing in it. – user16666480 Sep 01 '21 at 04:30
in this line df = df.fillna(value = "[]") replace [] with None or Nan as this df = df.fillna(value = "None") . Does this help ? – Nukala Raghava Aditya Sep 01 '21 at 07:23
It didnt help but the reason the empty string didn't work was some had whitespace or new line etc... – user16666480 Sep 03 '21 at 01:31
Try this df.replace('[^A-Za-z0-9]+', np.nan, inplace=True,regex=True) df.replace('', np.nan, inplace=True) – Nukala Raghava Aditya Sep 04 '21 at 14:57
what I got to work was a regex replace looking for all instances of white space and another looking for any instance of \n\r etc.. – user16666480 Sep 07 '21 at 15:07

why is df.fillna() only filling some rows and the first column

1 Answers1