pandas drop columns with all nan code example

Example 1: drop if nan in column pandas

df = df[df['EPS'].notna()]

Example 2: dropping nan in pandas dataframe

df.dropna(subset=['name', 'born'])

Example 3: drop na pandas

>>> df.dropna(subset=['name', 'born'])
       name        toy       born
1    Batman  Batmobile 1940-04-25

Example 4: 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

Example 5: when converting from dataframe to list delete nan values

a = [[y for y in x if pd.notna(y)] for x in df.values.tolist()]
print (a)
[['str', 'aad', 'asd'], ['ddd'], ['xyz', 'abc'], ['btc', 'trz', 'abd']]