df_1 = pd.read_excel(os.path.join(directory,'copy.xlsm'), sheet_name= "weekly",header= None)
df_1 = df_1.drop(df_1.columns[[0,1]], axis=1)
df_1.columns = df_1.loc[3].rename(None)
df_1 = df_1.drop(range(5))

df_1.to_csv(directory + '1.csv', index=False, header= True)

df=pd.read_csv(os.path.join(directory,'1.csv'))



cols =['Order Qty (SL)','Confirmed Qty (SL)','Unconfirmed Qty (SL)','Cancelled Qty (SL)','Open Qty (SL)','Reserved Qty (SL)',

    'Fixed Qty (SL)','% Allocation (SL)','Delivered Qty (SL)','PGI Qty (SL)','Invoiced Qty (SL)',
    'Net Unit Price','Confirmed Net Value (SL)','Dollars Shipped (SL)','% Shipped/Allocated (SL)']

df.loc[:len(df) - 2, cols].replace(',', '', regex=True).apply(pd.to_numeric).dtypes.unique()


df[['Order Qty (SL)','Confirmed Qty (SL)','Unconfirmed Qty (SL)','Cancelled Qty (SL)','Open Qty (SL)','Reserved Qty (SL)',

    'Fixed Qty (SL)','% Allocation (SL)','Delivered Qty (SL)','PGI Qty (SL)','Invoiced Qty (SL)',
    'Net Unit Price','Confirmed Net Value (SL)','Dollars Shipped (SL)','% Shipped/Allocated (SL)']] /= 1000

print(df.head())