pandas Missing Data
Missing Data
Using fillna and dropna we can handling missing data.
# using dropna we can drop the data whcih will have nan
import numpy as np
import pandas as pd
df = pd.DataFrame({'A':[1,2,np.nan],
'B':[5,np.nan,np.nan],
'C':[1,2,3]})
df.dropna() # which will drop The nan rows
df.dropna(axis=1) # which will drop the nan columns
df.dropna(thresh=2) # it will drop those row which will 2 or more nan values
# using fillna we can fill the replace the nan on given value in fillna
import numpy as np
import pandas as pd
df = pd.DataFrame({'A':[1,2,np.nan],
'B':[5,np.nan,np.nan],
'C':[1,2,3]})
df.fillna(value='FILL VALUE')
df['A'].fillna(value=df['A'].mean())