Answers for "pandas drop columns that are all nan"

5

how to delete na values in a dataframe

# if you want to delete rows containing NA values
df.dropna(inplace=True)
Posted by: Guest on May-16-2020
25

drop if nan in column pandas

df = df[df['EPS'].notna()]
Posted by: Guest on March-17-2020
5

dropping nan in pandas dataframe

df.dropna(subset=['name', 'born'])
Posted by: Guest on April-27-2020
2

pandas drop rows with nan in a particular column

In [30]: df.dropna(subset=[1])   #Drop only if NaN in specific column (as asked in the question)
Out[30]:
          0         1         2
1  2.677677 -1.466923 -0.750366
2       NaN  0.798002 -0.906038
3  0.672201  0.964789       NaN
5 -1.250970  0.030561 -2.678622
6       NaN  1.036043       NaN
7  0.049896 -0.308003  0.823295
9 -0.310130  0.078891       NaN
Posted by: Guest on March-07-2021
0

select only some rows pandas

df.loc[df['column_name'].isin(some_values)]
Posted by: Guest on April-23-2020
0

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
Posted by: Guest on March-19-2020

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