drop columns with nan pandas

>>> df.dropna(axis='columns')
       name
0    Alfred
1    Batman
2  Catwoman

>>> df.dropna()
     name        toy       born
1  Batman  Batmobile 1940-04-25

df[~np.isnan(df)]

df = pd.DataFrame({"name": ['Alfred', 'Batman', 'Catwoman'],
...                    "toy": [np.nan, 'Batmobile', 'Bullwhip'],
...                    "born": [pd.NaT, pd.Timestamp("1940-04-25"),
...                             pd.NaT]})
>>> df
       name        toy       born
0    Alfred        NaN        NaT
1    Batman  Batmobile 1940-04-25
2  Catwoman   Bullwhip        NaT

##Drop the rows where at least one element is missing.
>>> df.dropna()
     name        toy       born
1  Batman  Batmobile 1940-04-25

# importing pandas as pd 
import pandas as pd 
  
# Creating the Index 
idx = pd.Index(['Jan', 'Feb', 'Mar', None, 'May', 'Jun', 
                None, 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']) 
  
# Print the Index 
idx