NaN-6.py

In [27]:
df.to_csv('Df_with_NaNs', index=False)

In [57]:
new_df = pd.read_csv('Df_with_NaNs', na_values= ['missing', 'not available', 'NA'])
# we should avoid adding the '#$%' value here as a value might be inappropriate
# in one column but not in another.
# eg: 'Male' entered as a value in Age column instead of Gender. 

# Setting new index with the same name
new_df['index'] = 'i0,i1,i2,i3,i4,i5'.split(',')
new_df.set_index('index', inplace=True)

#DataFrame is ready !
new_df

Out[57]:
	      c0 	  c1 	  c2 	  c3
index 				
i0 	    1.0 	2.0 	NaN 	3
i1 	    NaN 	NaN 	NaN 	NaN
i2 	    4.0 	5.0 	NaN 	#$%
i3 	    6.0 	7.0 	NaN 	8
i4 	    NaN 	9.0 	NaN 	10
i5          11.0        12.0    NaN     NaN