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- '''
- Created on Feb 14, 2020
- @author: deeejas
- '''
- import pandas as pd
- dtypes={'NETWEIGHT': 'int64', 'NETVALUE': 'int64'}
- df = pd.read_excel('intrastat.xlsx', dtype=dtypes) #, parse_dates=True, date_parser='DATA'
- # df['VSCODE'].dtype =
- # print(df['DATA'])
- # print(df['VSCODE'])
- # print(df.groupby(['VSCODE',
- # 'ACode', 'Bcode', 'DeliveryTermsCode',
- # 'TransportCode', 'CountryOfOrigin',
- # 'EXP'])['NETVALUE', 'NETWEIGHT'].sum())
- # print(df['VSCODE'])
- grouped_df = df.groupby(['VSCODE', 'ACode', 'Bcode', 'DeliveryTermsCode',
- 'TransportCode', 'CountryOfOrigin',
- 'EXP', 'SUPPL'])[['NETVALUE', 'NETWEIGHT', 'Q', 'SUPPLVALUE']].sum()
- print(grouped_df.index[0][7])
- # print(grouped_df.index[1][0])
- # print(grouped_df.columns)
- # for i in range(1, len(grouped_df)+1):
- # print(grouped_df['VSCODE'])
- # print(df_gr['NETVAELUE'].sum())
- # for columns in df.groupby(['VSCODE', 'EXP']).sum():
- # print(columns.title())
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