Substitute Empty Cells by NaN in pandas DataFrame in Python (Example Code)

import pandas as pd                                          # Load pandas library

import pandas as pd # Load pandas library

my_df = pd.DataFrame({'A':[5,' ', 5, '   ', 5, 5],           # Construct example DataFrame in Python
                      'B':['x','y', 'z', '', 'x', 'y']})
print(my_df)                                                 # Display example DataFrame in console
#      A  B
# 0    5  x
# 1       y
# 2    5  z
# 3        
# 4    5  x
# 5    5  y

my_df = pd.DataFrame({'A':[5,' ', 5, ' ', 5, 5], # Construct example DataFrame in Python 'B':['x','y', 'z', '', 'x', 'y']}) print(my_df) # Display example DataFrame in console # A B # 0 5 x # 1 y # 2 5 z # 3 # 4 5 x # 5 5 y

my_df = my_df.replace(r'^s*$', float('NaN'), regex = True)  # Exchanging blanks by NaN
print(my_df)                                                 # Displaying updated DataFrame
#      A    B
# 0  5.0    x
# 1  NaN    y
# 2  5.0    z
# 3  NaN  NaN
# 4  5.0    x
# 5  5.0    y

my_df = my_df.replace(r'^s*$', float('NaN'), regex = True) # Exchanging blanks by NaN print(my_df) # Displaying updated DataFrame # A B # 0 5.0 x # 1 NaN y # 2 5.0 z # 3 NaN NaN # 4 5.0 x # 5 5.0 y