remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')
remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')
remove row if all are the same value pandas
print (df['S'] != df['T'])
0 False
1 True
2 True
3 True
4 False
5 True
6 True
7 True
8 False
dtype: bool
df = df[df['S'] != df['T']]
print (df)
S T W U
1 A B 0 Undirected
2 A C 1 Undirected
3 B A 0 Undirected
5 B C 1 Undirected
6 C A 1 Undirected
7 C B 1 Undirected
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