Find out the percentage of missing values in each column in the given dataset

Question

import pandas as pd
df = pd.read_csv(\'https://query.data.world/s/Hfu_PsEuD1Z_yJHmGaxWTxvkz7W_b0\')
percent= 100*(len(df.loc[:,df.isnull().sum(axis=0)>=1 ].index) / l         


        

Answer 1

For me I did it like that :

def missing_percent(df):
        # Total missing values
        mis_val = df.isnull().sum()
        
        # Percentage of missing values
        mis_percent = 100 * df.isnull().sum() / len(df)
        
        # Make a table with the results
        mis_table = pd.concat([mis_val, mis_percent], axis=1)
        
        # Rename the columns
        mis_columns = mis_table.rename(
        columns = {0 : 'Missing Values', 1 : 'Percent of Total Values'})
        
        # Sort the table by percentage of missing descending
        mis_columns = mis_columns[
            mis_columns.iloc[:,1] != 0].sort_values(
        'Percent of Total Values', ascending=False).round(2)
        
        # Print some summary information
        print ("Your selected dataframe has " + str(df.shape[1]) + " columns.\n"      
            "There are " + str(mis_columns.shape[0]) +
              " columns that have missing values.")
        
        # Return the dataframe with missing information
        return mis_columns