text_plain_output_1.png image_output_1.png
from pandas import read_csv

from pandas import read_csv
train = read_csv('/kaggle/input/telecom-churn-case-study-hackathon-gc1/train.csv')
train = train.drop(['id', 'circle_id'], axis=1)
test = read_csv('/kaggle/input/telecom-churn-case-study-hackathon-gc1/test.csv')
sample = read_csv('/kaggle/input/telecom-churn-case-study-hackathon-gc1/sample.csv')
metadata = read_csv('/kaggle/input/telecom-churn-case-study-hackathon-gc1/data_dictionary.csv')

(train.isna().sum() / len(train) * 100).plot(ylim=(0, 100), figsize=(15, 5))