text_html_output_1.png
import pandas as pd

import numpy as np
import pandas as pd
from sklearn.feature_extraction.text import TfidfVectorizer
train = pd.read_csv('../input/train.csv')

train.toxic.value_counts()

pd.crosstab(train.toxic, train.severe_toxic)

pd.crosstab(train.toxic, [train.obscene, train.threat, train.insult, train.identity_hate])

pd.crosstab(train.severe_toxic, [train.obscene, train.threat, train.insult, train.identity_hate])

train.iloc[:, 2:8].corr()

train[train.comment_text.isnull()]

train[train.comment_text == '']

train['comment_length'] = train.comment_text.str.len()
train.comment_length.describe()