Remove NaN ‘Cells’ without dropping the entire ROW (Pandas,Python3)

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I think you can use this:

df = df.apply(lambda x: pd.Series(x.dropna().values))

For example:

import pandas as pd
import numpy as np

df = pd.DataFrame({
    'Word':['Hello', 'My', 'Yellow', 'Golden', 'Yellow'],
    'Word2':[np.nan, 'My Name', 'Yellow Bee', 'Golden Gates', np.nan],
    'Word3':[np.nan, np.nan, 'Yellow Bee Hive', np.nan, np.nan]
})

print(df)

Initial dataframe:

     Word         Word2            Word3
0   Hello           NaN              NaN
1      My       My Name              NaN
2  Yellow    Yellow Bee  Yellow Bee Hive
3  Golden  Golden Gates              NaN
4  Yellow           NaN              NaN

and applying this lambda function:

df = df.apply(lambda x: pd.Series(x.dropna().values))

print(df)

gives:

     Word         Word2            Word3
0   Hello       My Name  Yellow Bee Hive
1      My    Yellow Bee              NaN
2  Yellow  Golden Gates              NaN
3  Golden           NaN              NaN
4  Yellow           NaN              NaN

Then you can fill NaN values with empty strings:

df = df.fillna('')

print(df)

     Word         Word2            Word3
0   Hello       My Name  Yellow Bee Hive
1      My    Yellow Bee                 
2  Yellow  Golden Gates                 
3  Golden                               
4  Yellow

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