283 lines
12 KiB
Python
283 lines
12 KiB
Python
import glob
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import os
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import shutil
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import pandas as pd
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from openpyxl import load_workbook
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from openpyxl.styles import Font, PatternFill, Border, Side, Alignment
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from openpyxl.utils import get_column_letter
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from datetime import date, datetime
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# Paths
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src_dir = "U:/PythonProject/Janssen/Covance_UCO3001/"
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out_dir = "U:/Dropbox/!!!Days/Downloads Z230/"
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# Find source files
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src_files = glob.glob(src_dir + "3001Specimeninventoryreport*.xlsx")
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assert src_files, "Source file not found!"
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src_file = src_files[0]
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print(f"Source xlsx: {src_file}")
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csv_files = glob.glob(src_dir + "_EDCStdRpt-DataListing.csv")
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assert csv_files, "CSV file not found!"
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csv_file = csv_files[0]
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print(f"Source csv: {csv_file}")
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# Delete old output report if exists
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today = date.today().strftime("%Y-%m-%d")
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out_filename = f"{today} 77242113UCO3001 Speciment Inventory report.xlsx"
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out_path = out_dir + out_filename
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for old in glob.glob(out_dir + "*77242113UCO3001 Speciment Inventory report*.xlsx"):
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os.remove(old)
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print(f"Deleted old: {old}")
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# Copy source file to output — preserves all formatting perfectly
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shutil.copy2(src_file, out_path)
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# Load data with pandas for analysis
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df = pd.read_excel(src_file, sheet_name=0, header=2)
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# All unique patients
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all_patients = sorted(df['Patient Number'].dropna().unique())
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# BXSCR and DNA rows
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bxscr = df[df['Protocol Visit Code'] == 'BXSCR']
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dna = df[df['Protocol Visit Code'] == 'DNA']
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# Parse date value to datetime object
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def fmt_date(val):
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if pd.isna(val):
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return None
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if isinstance(val, str):
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return datetime.strptime(val, '%d-%b-%Y')
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return pd.to_datetime(val).to_pydatetime()
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# Get Container Receipt Date + Excel row for patient+specimen from given visit dataframe
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# Excel row = pandas df index + 4 (rows 1-2 title, row 3 header, data from row 4)
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def get_specimen_info(visit_df, patient, specimen_type=None):
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rows = visit_df[visit_df['Patient Number'] == patient]
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if specimen_type:
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rows = rows[rows['Specimen Type'] == specimen_type]
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if rows.empty:
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return '', None
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row = rows.iloc[0]
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return fmt_date(row['Container Receipt Date']), rows.index[0] + 4
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# Get Container Receipt Date + Excel row by Container Label Line 1 code and visit code
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def get_label_info(patient, label_code, visit_code):
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rows = df[(df['Patient Number'] == patient) &
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(df['Protocol Visit Code'] == visit_code) &
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(df['Container Label Line 1'] == label_code)]
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if rows.empty:
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return '', None
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row = rows.iloc[0]
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return fmt_date(row['Container Receipt Date']), rows.index[0] + 4
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# Open copied workbook and add analysis sheet
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out_wb = load_workbook(out_path)
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# Create analysis sheet
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analysis_ws = out_wb.create_sheet("Přehled vzorků")
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thin = Side(style='thin')
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border = Border(left=thin, right=thin, top=thin, bottom=thin)
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# Column definitions: (header, width)
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# No "Visit code" column
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columns = [
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("Investigator Name", 24),
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("Číslo pacienta", 20),
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("Máme biopsii SM11", 20), # col 3 → SCREENING C:E
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("Máme RNA", 16),
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("Máme Cryostor", 16),
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("DNA", 14), # col 6 → no group
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("PLASMPK I-0 TROUGH", 18), # col 7 → RANDOMIZACE I-0 G:L
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("PLASMA PK I-0 PEAK", 18),
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("SERUM ADA I-0 PRE", 18),
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("SM06/SERUM BIOM", 16),
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("SM07/WB RNA", 14),
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("SM10/FECAL", 14),
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("PLASMPK I-2 TROUGH", 18), # col 13 → I-2 M:P
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("PLASMA PK I-2 PEAK", 18),
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("SERUM ADA I-2 PRE", 18),
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("STOOL I-2", 12),
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("PLASMPK I-4 TROUGH", 18), # col 17 → I-4 Q:V
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("PLASMA PK I-4 PEAK", 18),
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("SERUM ADA I-4 PRE", 18),
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("SM06/SERUM BIOM", 16),
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("SM07/WB RNA", 14),
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("STOOL I-4", 12),
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]
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# Row 1 — group headers
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group_font = Font(name='Calibri', bold=True, size=11)
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group_fill = PatternFill("solid", fgColor="FFFFFF") # white, same as user's theme=0
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group_border = Border(left=thin, right=thin, top=thin, bottom=thin)
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groups = [
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(3, 5, "SCREENING"),
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(7, 12, "RANDOMIZACE I-0"),
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(13, 16, "I-2"),
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(17, 22, "I-4"),
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]
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for start_col, end_col, label in groups:
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analysis_ws.merge_cells(start_row=1, start_column=start_col, end_row=1, end_column=end_col)
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cell = analysis_ws.cell(row=1, column=start_col, value=label)
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cell.font = group_font
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cell.fill = group_fill
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cell.alignment = Alignment(horizontal='center', vertical='center')
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cell.border = group_border
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# apply border to all merged cells
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for c in range(start_col, end_col + 1):
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analysis_ws.cell(row=1, column=c).border = group_border
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analysis_ws.row_dimensions[1].height = 20
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# Row 2 — column headers
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header_fill = PatternFill("solid", fgColor="4472C4")
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header_font = Font(name='Calibri', bold=True, size=11, color="FFFFFF")
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for col_idx, (header, width) in enumerate(columns, 1):
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cell = analysis_ws.cell(row=2, column=col_idx, value=header)
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cell.font = header_font
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cell.fill = header_fill
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cell.border = border
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cell.alignment = Alignment(horizontal='center', vertical='center', wrap_text=True)
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analysis_ws.column_dimensions[get_column_letter(col_idx)].width = width
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analysis_ws.row_dimensions[2].height = 30
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# Freeze first 2 columns and first 2 rows
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analysis_ws.freeze_panes = "C3"
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# Data rows start at row 3
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date_font_link = Font(name='Calibri', size=11, color="000000", underline='single')
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yes_fill = PatternFill("solid", fgColor="E2EFDA")
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no_fill = PatternFill("solid", fgColor="FFE7E7")
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data_font = Font(name='Calibri', size=11)
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src_sheet_name = out_wb.sheetnames[0]
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pat_sheet_name = "Seznam pacientů"
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# Build patient → first Excel row in "Seznam pacientů" (header=row1, data from row2)
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# pat_df is built later, but we need sorted order — pre-sort here too
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_csv_df_pre = pd.read_csv(csv_file, encoding='utf-8')
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_pat_pre = _csv_df_pre[['SiteNumber', 'Subject', 'Field4Value']].copy()
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_pat_pre['Field4Value'] = _pat_pre['Field4Value'].apply(lambda v: datetime.strptime(str(v).strip(), '%d %b %Y') if pd.notna(v) else None)
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_pat_pre = _pat_pre.sort_values(['SiteNumber', 'Subject', 'Field4Value']).reset_index(drop=True)
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patient_row_map = {}
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for i, row in _pat_pre.iterrows():
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pat = row['Subject']
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if pat not in patient_row_map:
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patient_row_map[pat] = i + 2 # +1 for 1-based, +1 for header row
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# Only patients with any BXSCR record
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bxscr_patients = sorted(bxscr['Patient Number'].dropna().unique())
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for row_idx, patient in enumerate(bxscr_patients, 3):
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investigator = bxscr[bxscr['Patient Number'] == patient].iloc[0]['Investigator Name']
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sm11, sm11_row = get_specimen_info(bxscr, patient, 'Tissue , Paraffin Block')
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rna, rna_row = get_specimen_info(bxscr, patient, 'Biopsy RNA Later')
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cryo, cryo_row = get_specimen_info(bxscr, patient, 'Biopsy, Frozen Tissue')
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dna_date, dna_row = get_specimen_info(dna, patient)
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trough, trough_row = get_label_info(patient, 'PLASMPK I-0 TROUGH', 'I-0')
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peak, peak_row = get_label_info(patient, 'PLASMA PK I-0 PEAK', 'I-0')
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ada, ada_row = get_label_info(patient, 'SERUM ADA I-0 PRE', 'I-0')
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sm06, sm06_row = get_label_info(patient, 'SM06/SERUM BIOM', 'I-0')
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sm07, sm07_row = get_label_info(patient, 'SM07/WB RNA', 'I-0')
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sm10, sm10_row = get_label_info(patient, 'SM10/FECAL', 'I-0')
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trough2, trough2_row = get_label_info(patient, 'PLASMPK I-2 TROUGH', 'I-2')
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peak2, peak2_row = get_label_info(patient, 'PLASMA PK I-2 PEAK', 'I-2')
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ada2, ada2_row = get_label_info(patient, 'SERUM ADA I-2 PRE', 'I-2')
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stool2, stool2_row = get_label_info(patient, 'STOOL I-2', 'I-2')
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trough4, trough4_row = get_label_info(patient, 'PLASMPK I-4 TROUGH', 'I-4')
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peak4, peak4_row = get_label_info(patient, 'PLASMA PK I-4 PEAK', 'I-4')
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ada4, ada4_row = get_label_info(patient, 'SERUM ADA I-4 PRE', 'I-4')
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sm064, sm064_row = get_label_info(patient, 'SM06/SERUM BIOM', 'I-4')
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sm074, sm074_row = get_label_info(patient, 'SM07/WB RNA', 'I-4')
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stool4, stool4_row = get_label_info(patient, 'STOOL I-4', 'I-4')
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# col 1-2: plain text, col 3+: (date, excel_row) tuples
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row_data = [investigator, patient,
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(sm11, sm11_row), (rna, rna_row), (cryo, cryo_row), (dna_date, dna_row),
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(trough, trough_row), (peak, peak_row), (ada, ada_row),
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(sm06, sm06_row), (sm07, sm07_row), (sm10, sm10_row),
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(trough2, trough2_row), (peak2, peak2_row), (ada2, ada2_row), (stool2, stool2_row),
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(trough4, trough4_row), (peak4, peak4_row), (ada4, ada4_row),
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(sm064, sm064_row), (sm074, sm074_row), (stool4, stool4_row)]
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for col_idx, value in enumerate(row_data, 1):
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if col_idx <= 2:
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cell = analysis_ws.cell(row=row_idx, column=col_idx, value=value)
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if col_idx == 2 and patient in patient_row_map:
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cell.hyperlink = f"#'{pat_sheet_name}'!B{patient_row_map[patient]}"
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cell.font = Font(name='Calibri', size=11, underline='single')
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else:
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cell.font = data_font
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else:
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dt, excel_row = value
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cell = analysis_ws.cell(row=row_idx, column=col_idx, value=dt)
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if dt and excel_row is not None:
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cell.hyperlink = f"#'{src_sheet_name}'!A{excel_row}"
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cell.font = date_font_link
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cell.fill = yes_fill
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cell.number_format = 'DD-MMM-YYYY'
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else:
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cell.font = Font(name='Calibri', size=11, color="C00000")
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cell.fill = no_fill
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cell.border = border
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cell.alignment = Alignment(horizontal='center', vertical='center')
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# ── Seznam pacientů sheet ────────────────────────────────────────────────────
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csv_df = pd.read_csv(csv_file, encoding='utf-8')
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patients_ws = out_wb.create_sheet("Seznam pacientů")
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pat_columns = [
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("Číslo centra", 20),
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("Číslo pacienta", 20),
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("Kód návštěvy", 20),
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("Datum návštěvy", 16),
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("Typ návštěvy", 16),
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]
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# Header row
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for col_idx, (col_name, width) in enumerate(pat_columns, 1):
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cell = patients_ws.cell(row=1, column=col_idx, value=col_name)
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cell.font = header_font
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cell.fill = header_fill
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cell.border = border
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cell.alignment = Alignment(horizontal='center', vertical='center', wrap_text=True)
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patients_ws.column_dimensions[get_column_letter(col_idx)].width = width
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patients_ws.row_dimensions[1].height = 30
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patients_ws.freeze_panes = "A2"
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# Prepare and sort data
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def parse_date(val):
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if pd.isna(val) or str(val).strip() == '':
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return None
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try:
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return datetime.strptime(str(val).strip(), '%d %b %Y')
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except:
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return None
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pat_df = csv_df[['SiteNumber', 'Subject', 'InstanceName', 'Field4Value', 'Field5Value']].copy()
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pat_df['Field4Value'] = pat_df['Field4Value'].apply(parse_date)
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pat_df = pat_df.sort_values(['SiteNumber', 'Subject', 'Field4Value']).reset_index(drop=True)
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# Data rows
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for row_idx, row in enumerate(pat_df.itertuples(index=False), 2):
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for col_idx, value in enumerate(row, 1):
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cell = patients_ws.cell(row=row_idx, column=col_idx, value=value)
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cell.font = data_font
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cell.border = border
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cell.alignment = Alignment(horizontal='center', vertical='center')
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if col_idx == 4 and value is not None:
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cell.number_format = 'DD-MMM-YYYY'
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out_wb.save(out_path)
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print(f"Saved: {out_path}")
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print(f"Patients with BXSCR: {len(bxscr_patients)}")
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print(f"All unique patients: {len(all_patients)}")
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