text_plain_output_1.png
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import seaborn as sns

train_df = pd.read_csv('../input/train.csv')
test_df = pd.read_csv('../input/test.csv')
sample_sub_df = pd.read_csv('../input/train.csv')

train_df[train_df.id_code == '5d024177e214']

classes_dist = pd.DataFrame(train_df['diagnosis'].value_counts() / train_df.shape[0]).reset_index()
ax = sns.barplot(x='index', y='diagnosis', data=classes_dist)