text_plain_output_35.png text_plain_output_43.png text_plain_output_37.png text_plain_output_5.png text_plain_output_48.png text_plain_output_30.png text_plain_output_15.png text_plain_output_9.png text_plain_output_44.png text_plain_output_40.png text_plain_output_31.png text_plain_output_20.png text_plain_output_4.png text_plain_output_13.png text_plain_output_45.png text_plain_output_14.png text_plain_output_32.png text_plain_output_29.png text_plain_output_49.png text_plain_output_27.png text_plain_output_10.png text_plain_output_6.png text_plain_output_24.png text_plain_output_21.png text_plain_output_47.png text_plain_output_25.png text_plain_output_18.png text_plain_output_50.png text_plain_output_36.png text_plain_output_3.png text_plain_output_22.png text_plain_output_38.png text_plain_output_7.png text_plain_output_16.png text_plain_output_8.png text_plain_output_26.png text_plain_output_41.png text_plain_output_34.png text_plain_output_42.png text_plain_output_23.png text_plain_output_51.png text_plain_output_28.png text_plain_output_2.png text_plain_output_33.png application_vnd.jupyter.stderr_output_1.png text_plain_output_39.png text_plain_output_19.png text_plain_output_17.png text_plain_output_11.png text_plain_output_12.png text_plain_output_46.png
import pandas as pd

data = pd.read_csv('/kaggle/input/quora-question-pairs/train.csv.zip')

pd.set_option('display.max_colwidth', 100)

data.rename(columns={'is_duplicate': 'similar'}, inplace=True)

data.drop(['id', 'qid1', 'qid2'], axis=1, inplace=True)

print(data['similar'].value_counts())
print(data['similar'].value_counts() / data['similar'].count() * 100)
data['similar'].value_counts().plot(kind='bar')