Advertisement
Not a member of Pastebin yet?
Sign Up,
it unlocks many cool features!
- OrderNo NetPerPiece costsDividedPerOrder HandlingPerPiece
- 0 7027514279 44.24 0.008007 0.354232
- 1 7027514279 15.93 0.008007 0.127552
- 2 7027514279 15.93 0.008007 0.127552
- 3 7027514279 15.93 0.008007 0.127552
- 4 7027514279 15.93 0.008007 0.127552
- surcharges = {'surcharge': [0.35, 0.25, 0.2, 0.15, 0.12, 0.1],
- 'from': [0, 20, 200, 500, 1500, 5000],
- 'to' : [20, 200, 500, 1500, 5000,1000000000] }
- surchargeTable = DataFrame(surcharges, columns=['surcharge', 'from', 'to'])
- productsPerOrder['NetPerpieceSale'] = numpy.where(((productsPerOrder['NetPerPiece'] >= surchargeTable['from']) & (productsPerOrder['NetPerPiece'] < surchargeTable['to'])), surchargeTable['surcharge'])
- #I also tried this:
- for index, row in productsPerOrder.iterrows():
- if row['NetPerPiece'] >= surchargeTable['from'] & row['NetPerPiece'] < surchargeTable['to']:
- productsPerOrder.loc[index,'NerPerPieceSale'] = surchargeTable.loc[row,'NetPerPieceSale'].values(0)
- OrderNo NetPerPiece costsDividedPerOrder HandlingPerPiece NetPerPieceSale
- 0 7027514279 44.24 0.008007 0.354232 0.25
- 1 7027514279 15.93 0.008007 0.127552 0.35
- 2 7027514279 15.93 0.008007 0.127552 0.35
- 3 7027514279 15.93 0.008007 0.127552 0.35
- 4 7027514279 15.93 0.008007 0.127552 0.35
Advertisement
Add Comment
Please, Sign In to add comment
Advertisement