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

Let's break down your ask

1. you want the percentage of missing value
2. it should be sorted in ascending order and the values to be rounded to 2 floating point

Explanation:

1. dhr[fill_cols].isnull().sum() - gives the total number of missing values column wise
2. dhr.shape[0] - gives the total number of rows
3. (dhr[fill_cols].isnull().sum()/dhr.shape[0]) - gives you a series with percentage as values and column names as index
4. since the output is a series you can round and sort based on the values

code:

(dhr[fill_cols].isnull().sum()/dhr.shape[0]).round(2).sort_values()

Reference: sort, round