text_plain_output_1.png
import numpy as np

import pandas as pd

dataset = pd.read_csv('/kaggle/input/house-prices-advanced-regression-techniques/train.csv')

dataset.isnull().sum()

features_with_na = []
for features in dataset.columns:
    if dataset[features].isnull().sum() > 1:
        features_with_na.append(features)
features_with_na

features_with_na = [features for features in dataset.columns if dataset[features].isnull().sum() > 1]
for feature in features_with_na:
    print(feature, np.round(dataset[feature].isnull().mean(), 4), ' % missing values')