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添加汇总，barcode非16位，则按后8位处理

new_sanwei
chaopower 2024-05-07 17:59:42 +08:00
parent 82c31b8d56
commit 796b2deef4
1 changed files with 22 additions and 2 deletions
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24
tools/t7.py
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@ -493,12 +493,14 @@ class AutoLayout:
# 非正常barcode # 非正常barcode
barcode_mask = ori_library_df['indexi5i7'].str.len() != 16 barcode_mask = ori_library_df['indexi5i7'].str.len() != 16
ori_library_df.loc[barcode_mask, 'indexi5i7'] = ori_library_df.loc[barcode_mask, 'indexi5'].str[-8:] + \
ori_library_df.loc[barcode_mask, 'indexi7'].str[-8:]
ori_library_df['note'] = '' ori_library_df['note'] = ''
ori_library_df.loc[~numeric_mask, 'note'] = 'data_needed 列非数字' ori_library_df.loc[~numeric_mask, 'note'] = 'data_needed 列非数字'
ori_library_df.loc[~time_mask, 'note'] = 'time 列非日期' ori_library_df.loc[~time_mask, 'note'] = 'time 列非日期'
ori_library_df.loc[barcode_mask, 'note'] = '非16位barcode' # ori_library_df.loc[barcode_mask, 'note'] = '非16位barcode'
no_ori_data = ori_library_df[~(numeric_mask & time_mask) | barcode_mask] no_ori_data = ori_library_df[~(numeric_mask & time_mask)]
self.no_assign_data.extend(no_ori_data.to_dict('records')) self.no_assign_data.extend(no_ori_data.to_dict('records'))
@ -693,6 +695,7 @@ class AutoLayout:
writer = pd.ExcelWriter(outputpath) writer = pd.ExcelWriter(outputpath)
res = list() res = list()
sum_res = list()
chip_loc = 1 chip_loc = 1
librarynum = 0 librarynum = 0
for chip_idx, chip_assignments in self.index_assignments.items(): for chip_idx, chip_assignments in self.index_assignments.items():
@ -725,10 +728,27 @@ class AutoLayout:
# df.to_excel(writer, sheet_name=chipname, index=False) # df.to_excel(writer, sheet_name=chipname, index=False)
res.extend(df.to_dict('records')) res.extend(df.to_dict('records'))
chip_loc += 1 chip_loc += 1
sum_list = list()
for library, library_df in df.groupby('samplename'):
sum_list.append(dict(
二次拆分=library,
客户=library_df['companynamea'].values[0],
类型=library_df['classification'].values[0],
打折前=library_df['orderdatavolume'].sum()
))
df_sum = pd.DataFrame(sum_list)
sum_res.append({'sheetname': chipname, 'data': df_sum})
res_df = pd.DataFrame(res) res_df = pd.DataFrame(res)
res_df = pd.concat([pd.DataFrame(self.items), res_df]).reset_index(drop=True) res_df = pd.concat([pd.DataFrame(self.items), res_df]).reset_index(drop=True)
res_df.to_excel(writer, sheet_name='assignment', index=False) res_df.to_excel(writer, sheet_name='assignment', index=False)
for sum_sheet in sum_res:
sheetname = sum_sheet.get('sheetname')
df_data = sum_sheet.get('data')
df_data.to_excel(writer, sheet_name=sheetname, index=False)
no_assign_df = pd.DataFrame(self.no_assign_data) no_assign_df = pd.DataFrame(self.no_assign_data)
if not no_assign_df.empty: if not no_assign_df.empty:
no_assign_df = no_assign_df.applymap(lambda x: format_date(x) if isinstance(x, pd.Timestamp) else x) no_assign_df = no_assign_df.applymap(lambda x: format_date(x) if isinstance(x, pd.Timestamp) else x)