Drop the rows where all elements are missing in a DataFrame

In this python pandas program, we will drop the rows where all elements are missing in a DataFrame using the pandas library.

Steps to solve the program
  1. Import pandas library as pd.
  2. Create a dataframe using pd.DataFrame().
  3. Now drop the rows where all elements are missing using df.dropna(how=’all’).
  4. Print the output.
				
					import pandas as pd
import numpy as np
df = pd.DataFrame({'Sr.no.':[1,np.nan,3,4],
                   'Name':['Alex',np.nan,'Peter','Klaus'],
                   'Age':[30,np.nan,29,np.nan]})
print("Original Dataframe: \n",df)
print("Drop the rows where all elements are missing:")
result = df.dropna(how='all')
print(result)
				
			

Output :

				
					Original Dataframe: 
    Sr.no.   Name   Age
0     1.0   Alex  30.0
1     NaN    NaN   NaN
2     3.0  Peter  29.0
3     4.0  Klaus   NaN
Drop the rows where all elements are missing:
   Sr.no.   Name   Age
0     1.0   Alex  30.0
2     3.0  Peter  29.0
3     4.0  Klaus   NaN
				
			

drop the columns where at least one element is missing in a DataFrame

replace NaNs with the value from the previous row in a DataFrame

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