text_html_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

import seaborn as sns

df_train = pd.read_csv('../input/train.csv')
df_store = pd.read_csv('../input/store.csv')
df_test = pd.read_csv('../input/test.csv')

fig, (axis1) = plt.subplots(1,1,figsize=(15,4))
sns.countplot(x = 'Open', hue = 'DayOfWeek', data = df_train,)

df_train['Year'] = df_train['Date'].apply(lambda x: int(x[:4]))

df_train['Month'] = df_train['Date'].apply(lambda x: int(x[5:7]))

average_monthly_sales = df_train.groupby('Month')['Sales'].mean()
fig = plt.subplots(1, 1, sharex=True, figsize=(10, 5))
average_monthly_sales.plot(legend=True, marker='o', title='Average Sales')