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g96
Feb 18th, 2022
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  1. df[['Order Qty (SL)','Confirmed Qty (SL)','Unconfirmed Qty (SL)','Cancelled Qty (SL)','Open Qty (SL)','Reserved Qty (SL)',
  2.  
  3.     'Fixed Qty (SL)','% Allocation (SL)','Delivered Qty (SL)','PGI Qty (SL)','Invoiced Qty (SL)',
  4.     'Net Unit Price','Confirmed Net Value (SL)','Dollars Shipped (SL)','% Shipped/Allocated (SL)']] = pd.to_numeric(df['Order Qty (SL)','Confirmed Qty (SL)','Unconfirmed Qty (SL)',
  5.                                                                                                                        'Cancelled Qty (SL)','Open Qty (SL)','Reserved Qty (SL)',
  6.  
  7.     'Fixed Qty (SL)','% Allocation (SL)','Delivered Qty (SL)','PGI Qty (SL)','Invoiced Qty (SL)',
  8.     'Net Unit Price','Confirmed Net Value (SL)','Dollars Shipped (SL)','% Shipped/Allocated (SL)'], errors='coerce')
  9.  
  10. df[['Order Qty (SL)','Confirmed Qty (SL)','Unconfirmed Qty (SL)','Cancelled Qty (SL)','Open Qty (SL)','Reserved Qty (SL)',
  11.  
  12.     'Fixed Qty (SL)','% Allocation (SL)','Delivered Qty (SL)','PGI Qty (SL)','Invoiced Qty (SL)',
  13.     'Net Unit Price','Confirmed Net Value (SL)','Dollars Shipped (SL)','% Shipped/Allocated (SL)']] /= 1000
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