Drop Rows with Blank Values from pandas DataFrame in Python (3 Examples) | replace() & NaN Missings

Python code of this video:

import pandas as pd # Load pandas

data = pd.DataFrame({'x1':[1, '', ' ', 2, 3, 4], # Create example DataFrame
'x2':['', '', 'a', 'b', 'c', 'd'],
'x3':[' ', 'a', 'b', 'c', 'd', '']})
print(data) # Print example DataFrame
# x1 x2 x3
# 0 1
# 1 a
# 2 a b
# 3 2 b c
# 4 3 c d
# 5 4 d

print(data_new1) # Print updated data
# x1 x2 x3
# 0 1.0 NaN NaN
# 1 NaN NaN a
# 2 NaN a b
# 3 2.0 b c
# 4 3.0 c d
# 5 4.0 d NaN

print(data_new2) # Print updated data
# x1 x2 x3
# 3 2.0 b c
# 4 3.0 c d

print(data_new3) # Print updated data
# x1 x2 x3
# 0 1.0 NaN NaN
# 3 2.0 b c
# 4 3.0 c d
# 5 4.0 d NaN

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