text_plain_output_1.png
import matplotlib.pyplot as plt

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

import seaborn as sns

train = pd.read_csv('/kaggle/input/rossmann-store-sales/train.csv')
test = pd.read_csv('/kaggle/input/rossmann-store-sales/test.csv')
store = pd.read_csv('/kaggle/input/rossmann-store-sales/store.csv')

train = train[train['Sales'] > 0]

train['Date'] = pd.to_datetime(train['Date'])
train.sort_values(by='Date', ascending=True, inplace=True)
train.reset_index(inplace=True)
train.drop('index', axis=1, inplace=True)
start_date = train['Date'][0]
end_date = train['Date'][844337]

pd.options.display.float_format = '{:.0f}'.format

plt.figure(figsize=(15, 8))
sns.scatterplot(x='Sales', y='Customers', data=train, hue='DayOfWeek', palette='coolwarm')
plt.show()
plt.figure(figsize=(15, 4))
print(train['DayOfWeek'].value_counts())
sns.countplot('DayOfWeek', data=train, palette='coolwarm')
plt.show()
g = sns.FacetGrid(row='DayOfWeek', data=train, height=3, aspect=4)
g.map(plt.scatter, 'Sales', 'Customers')
plt.show()
plt.figure(figsize=(15, 8))
sns.boxplot(y='Sales', x='DayOfWeek', data=train, palette='coolwarm')
plt.show()
plt.figure(figsize=(15, 8))
sns.boxplot(y='Customers', x='DayOfWeek', data=train, palette='coolwarm')
plt.show()