text_html_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

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

import seaborn as sns

sample = pd.read_csv('../input/lish-moa/sample_submission.csv')
test_f = pd.read_csv('../input/lish-moa/test_features.csv')
train_f = pd.read_csv('../input/lish-moa/train_features.csv')
drug = pd.read_csv('../input/lish-moa/train_drug.csv')
targ_nscore = pd.read_csv('../input/lish-moa/train_targets_nonscored.csv')
targ_score = pd.read_csv('../input/lish-moa/train_targets_scored.csv')

train = train_f.merge(targ_score, on='sig_id', how='left')
train = train.merge(targ_nscore, on='sig_id', how='left')

stargs_name = list(targ_score.columns[1:])
scored_targets = train[list(targ_score.columns[1:])].sum(axis = 1)
nscored_targets = train[list(targ_nscore.columns[1:])].sum(axis = 1)

fig,axes = plt.subplots(figsize = (32,8),ncols = 2)
sns.countplot(scored_targets,ax = axes[0])
sns.countplot(nscored_targets,ax = axes[1])
# scored_targets

for i in range(2):
    axes[i].tick_params(axis = 'x',labelsize =20)
    axes[i].tick_params(axis = 'y', labelsize = 20)

axes[0].set_title(f'Training set unique scored per sample',size = 22 , pad = 22)  
axes[1].set_title(f'Training set unique not scored per sample',size = 22 , pad = 22)   
plt.show()

fig, axes = plt.subplots(figsize=(24, 24), nrows=3, ncols=2)
sns.countplot(train_f['cp_type'], ax=axes[0][0])
sns.countplot(test_f['cp_type'], ax=axes[0][1])
sns.countplot(train_f['cp_time'], ax=axes[1][0])
sns.countplot(test_f['cp_time'], ax=axes[1][1])
sns.countplot(train_f['cp_dose'], ax=axes[2][0])
sns.countplot(test_f['cp_dose'], ax=axes[2][1])
for i, f in enumerate(['cp_type', 'cp_time', 'cp_dose']):
    for j, d in enumerate(['training', 'test']):
        axes[i][j].set_title(f'{d} Set {f} Distribution', size=20, pad=15)