text_plain_output_1.png
import pandas as pd

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

walmart_data = pd.read_csv('../input/walmart-sales/Walmart_Store_sales.csv')

walmart_data_groupby = walmart_data.groupby('Store')['Weekly_Sales'].sum()

walmart_data_std = walmart_data.groupby('Store').agg({'Weekly_Sales': 'std'})

walmart_data_std = walmart_data.groupby('Store').agg({'Weekly_Sales': ['mean', 'std']})

walmart_data_Q32012 = walmart_data[(pd.to_datetime(walmart_data['Date']) >= pd.to_datetime('07-01-2012')) & (pd.to_datetime(walmart_data['Date']) <= pd.to_datetime('09-30-2012'))]
walmart_data_growth = walmart_data_Q32012.groupby(['Store'])['Weekly_Sales'].sum()
print("Store Number {} has Good Quartely Growth in Q3'2012 {}".format(walmart_data_growth.idxmax(), walmart_data_growth.max()))