python3 -c " import openpyxl wb = openpyxl.load_workbook('/home/daytona/workspace/attachments/44a34df6-ea90-4821-87a9-f59d396c13db/ARTICLE SMITA-updated GFR.xlsx') print('Sheets:', wb.sheetnames) ws = wb.active print('Dimensions:', ws.dimensions) print('Max row:', ws.max_row, 'Max col:', ws.max_column) # Print first 3 rows to see headers for row in ws.iter_rows(min_row=1, max_row=3, values_only=True): print(row) "

python3 -c " import openpyxl wb = openpyxl.load_workbook('/home/daytona/workspace/attachments/44a34df6-ea90-4821-87a9-f59d396c13db/ARTICLE SMITA-updated GFR.xlsx') print('=== Sheet: Male ===') ws = wb['Male'] for row in ws.iter_rows(values_only=True): print(row) print() print('=== Sheet: Sheet3 ===') ws2 = wb['Sheet3'] print('Dimensions:', ws2.dimensions) print('Max row:', ws2.max_row, 'Max col:', ws2.max_column) for row in ws2.iter_rows(min_row=1, max_row=5, values_only=True): print(row) "

python3 << 'EOF' import openpyxl import math from scipy import stats import numpy as np wb = openpyxl.load_workbook('/home/daytona/workspace/attachments/44a34df6-ea90-4821-87a9-f59d396c13db/ARTICLE SMITA-updated GFR.xlsx') ws = wb['Male'] # Column indices (0-based from row): AGE=3(D), CREAT=4(F->col5?), CHOL=5, TG=6, HDL=7, LDL=8, VLDL=9, TC/HDL=10, LDL/HDL=11, CYS-C=12(N), eGFR_Creat=14(P), eGFR_CysC=15(Q) # Let's confirm by checking headers row (row 3, index 2) headers = [cell.value for cell in ws[3]] print("Headers:", headers) print("Col count:", len(headers)) EOF

python3 << 'EOF' import openpyxl import math from scipy import stats import numpy as np wb = openpyxl.load_workbook('/home/daytona/workspace/attachments/44a34df6-ea90-4821-87a9-f59d396c13db/ARTICLE SMITA-updated GFR.xlsx') ws = wb['Male'] # Column indices (1-based): A=1,B=2,C=3,D=4(AGE),E=5(UREA),F=6(CREAT),G=7(CHOL/TC),H=8(TG),I=9(HDL),J=10(LDL),K=11(VLDL),L=12(TC/HDL),M=13(LDL/HDL),N=14(CYS-C),O=15(empty),P=16(eGFR Creat),Q=17(eGFR CysC) data = { 'TC': [], 'TG': [], 'HDL': [], 'LDL': [], 'VLDL': [], 'TC_HDL': [], 'LDL_HDL': [], 'AGE': [], 'CYS_C': [], 'CREAT': [], 'eGFR_Creat': [], 'eGFR_CysC': [] } for row in ws.iter_rows(min_row=4, max_row=ws.max_row, values_only=True): if row[0] is None: continue age = row[3] # D creat = row[5] # F tc = row[6] # G tg = row[7] # H hdl = row[8] # I ldl = row[9] # J vldl = row[10] # K tc_hdl = row[11] # L ldl_hdl = row[12] # M cys_c = row[13] # N sex = row[2] # C # Compute eGFR values manually if age and creat and isinstance(creat, (int, float)): if sex == 'Male': egfr_creat = 175 * (creat**-1.154) * (age**-0.203) else: egfr_creat = 175 * (creat**-1.154) * (age**-0.203) * 0.742 else: egfr_creat = None if age and cys_c and isinstance(cys_c, (int, float)): if sex == 'Male': egfr_cysc = 127.7 * (cys_c**-1.17) * (age**-0.13) else: egfr_cysc = 127.7 * (cys_c**-1.17) * (age**-0.13) * 0.91 else: egfr_cysc = None if all(v is not None for v in [tc, tg, hdl, ldl, vldl, tc_hdl, ldl_hdl, cys_c, creat, egfr_creat, egfr_cysc]): data['TC'].append(tc) data['TG'].append(tg) data['HDL'].append(hdl) data['LDL'].append(ldl) data['VLDL'].append(vldl) data['TC_HDL'].append(tc_hdl) data['LDL_HDL'].append(ldl_hdl) data['CYS_C'].append(cys_c) data['CREAT'].append(creat) data['eGFR_Creat'].append(egfr_creat) data['eGFR_CysC'].append(egfr_cysc) data['AGE'].append(age) print(f"Total valid rows: {len(data['TC'])}") params = ['TC', 'TG', 'HDL', 'LDL', 'VLDL', 'TC_HDL', 'LDL_HDL'] param_labels = ['TC', 'TG', 'HDL', 'LDL', 'VLDL', 'TC/HDL', 'LDL/HDL'] print("\n{'Parameter': 'r_CysC', 'p_CysC', 'r_Creat', 'p_Creat'}") print("-"*60) results = [] for p, lbl in zip(params, param_labels): x = np.array(data[p]) r_cysc, p_cysc = stats.pearsonr(x, np.array(data['eGFR_CysC'])) r_creat, p_creat = stats.pearsonr(x, np.array(data['eGFR_Creat'])) results.append((lbl, r_cysc, p_cysc, r_creat, p_creat)) print(f"{lbl:10s} | r={r_cysc:+.4f}, p={p_cysc:.4f} | r={r_creat:+.4f}, p={p_creat:.4f}") # Now write to Sheet3 ws3 = wb['Sheet3'] # Row mapping: TC=3, TG=4, HDL=5, LDL=6, VLDL=7, TC/HDL=8, LDL/HDL=9 label_to_row = {'TC': 3, 'TG': 4, 'HDL': 5, 'LDL': 6, 'VLDL': 7, 'TC/HDL': 8, 'LDL/HDL': 9} for lbl, r_cysc, p_cysc, r_creat, p_creat in results: row_num = label_to_row.get(lbl) if row_num: ws3.cell(row=row_num, column=2, value=round(r_cysc, 4)) ws3.cell(row=row_num, column=3, value=round(p_cysc, 4)) ws3.cell(row=row_num, column=4, value=round(r_creat, 4)) ws3.cell(row=row_num, column=5, value=round(p_creat, 4)) # Also add LDL/HDL row if not present ws3.cell(row=9, column=1, value='LDL/HDL') import os os.makedirs('/home/daytona/workspace/smita-gfr/', exist_ok=True) out_path = '/home/daytona/workspace/smita-gfr/ARTICLE_SMITA_GFR_Correlations.xlsx' wb.save(out_path) print(f"\nSaved to {out_path}") EOF

python3 << 'EOF' import openpyxl from openpyxl.styles import Font, PatternFill, Alignment, Border, Side, numbers from openpyxl.utils import get_column_letter from scipy import stats import numpy as np import os # Re-read data wb_src = openpyxl.load_workbook('/home/daytona/workspace/attachments/44a34df6-ea90-4821-87a9-f59d396c13db/ARTICLE SMITA-updated GFR.xlsx') ws = wb_src['Male'] data = {k: [] for k in ['TC','TG','HDL','LDL','VLDL','TC_HDL','LDL_HDL','CYS_C','CREAT','eGFR_Creat','eGFR_CysC']} for row in ws.iter_rows(min_row=4, max_row=ws.max_row, values_only=True): if row[0] is None: continue age=row[3]; creat=row[5]; tc=row[6]; tg=row[7]; hdl=row[8] ldl=row[9]; vldl=row[10]; tc_hdl=row[11]; ldl_hdl=row[12]; cys_c=row[13]; sex=row[2] if sex=='Male': egfr_creat = 175*(creat**-1.154)*(age**-0.203) if (age and creat) else None egfr_cysc = 127.7*(cys_c**-1.17)*(age**-0.13) if (age and cys_c) else None else: egfr_creat = 175*(creat**-1.154)*(age**-0.203)*0.742 if (age and creat) else None egfr_cysc = 127.7*(cys_c**-1.17)*(age**-0.13)*0.91 if (age and cys_c) else None if all(v is not None for v in [tc,tg,hdl,ldl,vldl,tc_hdl,ldl_hdl,cys_c,creat,egfr_creat,egfr_cysc]): data['TC'].append(tc); data['TG'].append(tg); data['HDL'].append(hdl) data['LDL'].append(ldl); data['VLDL'].append(vldl) data['TC_HDL'].append(tc_hdl); data['LDL_HDL'].append(ldl_hdl) data['CYS_C'].append(cys_c); data['CREAT'].append(creat) data['eGFR_Creat'].append(egfr_creat); data['eGFR_CysC'].append(egfr_cysc) params = ['TC','TG','HDL','LDL','VLDL','TC_HDL','LDL_HDL'] labels = ['TC','TG','HDL','LDL','VLDL','TC/HDL','LDL/HDL'] results = [] for p,lbl in zip(params,labels): x = np.array(data[p]) r1,p1 = stats.pearsonr(x, np.array(data['eGFR_CysC'])) r2,p2 = stats.pearsonr(x, np.array(data['eGFR_Creat'])) sig1 = 'Significant' if p1<0.05 else 'Not Significant' sig2 = 'Significant' if p2<0.05 else 'Not Significant' results.append((lbl, round(r1,4), round(p1,4), sig1, round(r2,4), round(p2,4), sig2)) # Build fresh workbook wb = openpyxl.Workbook() ws_out = wb.active ws_out.title = 'Correlation Results' # Styles hdr_font = Font(name='Arial', bold=True, color='FFFFFF', size=11) hdr_fill = PatternFill('solid', fgColor='1F4E79') sub_fill = PatternFill('solid', fgColor='2E75B6') sub_font = Font(name='Arial', bold=True, color='FFFFFF', size=10) alt_fill = PatternFill('solid', fgColor='D9E1F2') norm_fill = PatternFill('solid', fgColor='FFFFFF') center = Alignment(horizontal='center', vertical='center', wrap_text=True) thin = Side(border_style='thin', color='B0B0B0') border = Border(left=thin, right=thin, top=thin, bottom=thin) # Title ws_out.merge_cells('A1:G1') ws_out['A1'] = 'Correlation of Lipid Parameters with eGFR (Cystatin C & Creatinine Based)' ws_out['A1'].font = Font(name='Arial', bold=True, size=14, color='1F4E79') ws_out['A1'].alignment = center ws_out.row_dimensions[1].height = 30 ws_out.merge_cells('A2:G2') ws_out['A2'] = f'n = {len(data["TC"])} patients | Pearson Correlation (r) and p-value' ws_out['A2'].font = Font(name='Arial', italic=True, size=10, color='404040') ws_out['A2'].alignment = center ws_out.row_dimensions[2].height = 18 # Group headers row 3 ws_out.merge_cells('B3:D3') ws_out.merge_cells('E3:G3') for cell, txt in [('A3','Parameter'), ('B3','eGFR - Cystatin C Based'), ('E3','eGFR - Creatinine Based')]: ws_out[cell] = txt ws_out[cell].font = hdr_font ws_out[cell].fill = hdr_fill ws_out[cell].alignment = center ws_out[cell].border = border ws_out.row_dimensions[3].height = 22 # Sub-headers row 4 for col, txt in [(1,'Parameter'),(2,'r'),(3,'p-value'),(4,'Significance'),(5,'r'),(6,'p-value'),(7,'Significance')]: c = ws_out.cell(row=4, column=col, value=txt) c.font = sub_font; c.fill = sub_fill; c.alignment = center; c.border = border ws_out.row_dimensions[4].height = 20 # Data rows for i, (lbl, r1, p1, sig1, r2, p2, sig2) in enumerate(results): row_num = i + 5 fill = alt_fill if i % 2 == 0 else norm_fill vals = [lbl, r1, p1, sig1, r2, p2, sig2] for col, val in enumerate(vals, 1): c = ws_out.cell(row=row_num, column=col, value=val) c.font = Font(name='Arial', size=10, bold=(col==1), color=('C00000' if 'Not Sig' in str(val) else ('375623' if 'Significant' in str(val) and 'Not' not in str(val) else '000000'))) c.fill = fill; c.alignment = center; c.border = border ws_out.row_dimensions[row_num].height = 18 # Column widths for col, w in [(1,14),(2,8),(3,10),(4,16),(5,8),(6,10),(7,16)]: ws_out.column_dimensions[get_column_letter(col)].width = w # Note row note_row = len(results) + 6 ws_out.merge_cells(f'A{note_row}:G{note_row}') ws_out[f'A{note_row}'] = 'Note: Significance threshold p < 0.05. eGFR Creatinine = MDRD formula; eGFR Cystatin C = Hoek formula.' ws_out[f'A{note_row}'].font = Font(name='Arial', italic=True, size=9, color='595959') ws_out[f'A{note_row}'].alignment = Alignment(horizontal='left') os.makedirs('/home/daytona/workspace/smita-gfr/', exist_ok=True) out_path = '/home/daytona/workspace/smita-gfr/ARTICLE_SMITA_GFR_Correlations.xlsx' wb.save(out_path) print(f"Saved: {out_path}") print("\nResults Summary:") print(f"{'Parameter':<12} {'r(CysC)':>9} {'p(CysC)':>9} {'Sig?':<18} {'r(Creat)':>10} {'p(Creat)':>10} {'Sig?'}") for row in results: print(f"{row[0]:<12} {row[1]:>9.4f} {row[2]:>9.4f} {row[3]:<18} {row[4]:>10.4f} {row[5]:>10.4f} {row[6]}") EOF

ls -la /home/daytona/workspace/smita-gfr/ 2>/dev/null || echo "dir not found" df -h /home/daytona/workspace/

mkdir -p /home/daytona/workspace/smita-gfr && ls -la /home/daytona/workspace/

python3 << 'EOF' # Test writing a simple xlsx first import openpyxl wb = openpyxl.Workbook() ws = wb.active ws['A1'] = 'Test' wb.save('/home/daytona/workspace/smita-gfr/test.xlsx') print("test write OK") import os os.remove('/home/daytona/workspace/smita-gfr/test.xlsx') print("removed test file") EOF

python3 << 'EOF' import openpyxl from openpyxl.styles import Font, PatternFill, Alignment, Border, Side from openpyxl.utils import get_column_letter from scipy import stats import numpy as np import shutil # Re-read data wb_src = openpyxl.load_workbook('/home/daytona/workspace/attachments/44a34df6-ea90-4821-87a9-f59d396c13db/ARTICLE SMITA-updated GFR.xlsx') ws = wb_src['Male'] data = {k: [] for k in ['TC','TG','HDL','LDL','VLDL','TC_HDL','LDL_HDL','CYS_C','CREAT','eGFR_Creat','eGFR_CysC']} for row in ws.iter_rows(min_row=4, max_row=ws.max_row, values_only=True): if row[0] is None: continue age=row[3]; creat=row[5]; tc=row[6]; tg=row[7]; hdl=row[8] ldl=row[9]; vldl=row[10]; tc_hdl=row[11]; ldl_hdl=row[12]; cys_c=row[13]; sex=row[2] if sex=='Male': egfr_creat = 175*(creat**-1.154)*(age**-0.203) if (age and creat) else None egfr_cysc = 127.7*(cys_c**-1.17)*(age**-0.13) if (age and cys_c) else None else: egfr_creat = 175*(creat**-1.154)*(age**-0.203)*0.742 if (age and creat) else None egfr_cysc = 127.7*(cys_c**-1.17)*(age**-0.13)*0.91 if (age and cys_c) else None if all(v is not None for v in [tc,tg,hdl,ldl,vldl,tc_hdl,ldl_hdl,cys_c,creat,egfr_creat,egfr_cysc]): data['TC'].append(tc); data['TG'].append(tg); data['HDL'].append(hdl) data['LDL'].append(ldl); data['VLDL'].append(vldl) data['TC_HDL'].append(tc_hdl); data['LDL_HDL'].append(ldl_hdl) data['CYS_C'].append(cys_c); data['CREAT'].append(creat) data['eGFR_Creat'].append(egfr_creat); data['eGFR_CysC'].append(egfr_cysc) params = ['TC','TG','HDL','LDL','VLDL','TC_HDL','LDL_HDL'] labels = ['TC','TG','HDL','LDL','VLDL','TC/HDL','LDL/HDL'] results = [] for p,lbl in zip(params,labels): x = np.array(data[p]) r1,p1 = stats.pearsonr(x, np.array(data['eGFR_CysC'])) r2,p2 = stats.pearsonr(x, np.array(data['eGFR_Creat'])) sig1 = 'Significant' if p1<0.05 else 'Not Significant' sig2 = 'Significant' if p2<0.05 else 'Not Significant' results.append((lbl, round(r1,4), round(p1,4), sig1, round(r2,4), round(p2,4), sig2)) # Build workbook wb = openpyxl.Workbook() ws_out = wb.active ws_out.title = 'Correlation Results' hdr_font = Font(name='Arial', bold=True, color='FFFFFF', size=11) hdr_fill = PatternFill('solid', fgColor='1F4E79') sub_fill = PatternFill('solid', fgColor='2E75B6') sub_font = Font(name='Arial', bold=True, color='FFFFFF', size=10) alt_fill = PatternFill('solid', fgColor='D9E1F2') norm_fill = PatternFill('solid', fgColor='FFFFFF') center = Alignment(horizontal='center', vertical='center', wrap_text=True) thin = Side(border_style='thin', color='B0B0B0') bdr = Border(left=thin, right=thin, top=thin, bottom=thin) ws_out.merge_cells('A1:G1') ws_out['A1'] = 'Correlation of Lipid Parameters with eGFR (Cystatin C & Creatinine Based)' ws_out['A1'].font = Font(name='Arial', bold=True, size=14, color='1F4E79') ws_out['A1'].alignment = center ws_out.row_dimensions[1].height = 32 ws_out.merge_cells('A2:G2') ws_out['A2'] = f'n = {len(data["TC"])} patients | Pearson Correlation (r) and p-value | Significance: p < 0.05' ws_out['A2'].font = Font(name='Arial', italic=True, size=10, color='404040') ws_out['A2'].alignment = center ws_out.row_dimensions[2].height = 18 ws_out.merge_cells('B3:D3') ws_out.merge_cells('E3:G3') for cell, txt in [('A3','Parameter'), ('B3','eGFR - Cystatin C Based'), ('E3','eGFR - Creatinine Based')]: ws_out[cell].value = txt ws_out[cell].font = hdr_font ws_out[cell].fill = hdr_fill ws_out[cell].alignment = center ws_out[cell].border = bdr ws_out.row_dimensions[3].height = 22 for col, txt in [(1,'Parameter'),(2,'r'),(3,'p-value'),(4,'Significance'),(5,'r'),(6,'p-value'),(7,'Significance')]: c = ws_out.cell(row=4, column=col, value=txt) c.font = sub_font; c.fill = sub_fill; c.alignment = center; c.border = bdr ws_out.row_dimensions[4].height = 20 for i, (lbl, r1, p1, sig1, r2, p2, sig2) in enumerate(results): row_num = i + 5 fill = alt_fill if i % 2 == 0 else norm_fill for col, val in enumerate([lbl, r1, p1, sig1, r2, p2, sig2], 1): c = ws_out.cell(row=row_num, column=col, value=val) color = '000000' if 'Not Significant' in str(val): color='C00000' elif str(val) == 'Significant': color='375623' c.font = Font(name='Arial', size=10, bold=(col==1), color=color) c.fill = fill; c.alignment = center; c.border = bdr ws_out.row_dimensions[row_num].height = 18 for col, w in [(1,14),(2,8),(3,10),(4,18),(5,8),(6,10),(7,18)]: ws_out.column_dimensions[get_column_letter(col)].width = w note_row = len(results) + 6 ws_out.merge_cells(f'A{note_row}:G{note_row}') ws_out[f'A{note_row}'] = 'Note: eGFR Creatinine = MDRD formula [175 x Creat^-1.154 x Age^-0.203 (x0.742 if female)]; eGFR Cystatin C = Hoek formula [127.7 x CysC^-1.17 x Age^-0.13 (x0.91 if female)].' ws_out[f'A{note_row}'].font = Font(name='Arial', italic=True, size=9, color='595959') ws_out[f'A{note_row}'].alignment = Alignment(horizontal='left') # Save to /tmp first, then copy to workspace tmp_path = '/tmp/ARTICLE_SMITA_GFR_Correlations.xlsx' out_path = '/home/daytona/workspace/smita-gfr/ARTICLE_SMITA_GFR_Correlations.xlsx' wb.save(tmp_path) shutil.copy2(tmp_path, out_path) print(f"Saved: {out_path}") print("\nResults:") print(f"{'Parameter':<12} {'r(CysC)':>9} {'p(CysC)':>9} {'':4} {'r(Creat)':>10} {'p(Creat)':>10}") for row in results: print(f"{row[0]:<12} {row[1]:>9.4f} {row[2]:>9.4f} {'*' if row[2]<0.05 else ' ':4} {row[4]:>10.4f} {row[5]:>10.4f} {'*' if row[5]<0.05 else ''}") EOF

# The directory disappears between commands on S3 - need to create and copy in one shot mkdir -p /home/daytona/workspace/smita-gfr && ls /home/daytona/workspace/smita-gfr && python3 -c " import shutil, os os.makedirs('/home/daytona/workspace/smita-gfr', exist_ok=True) shutil.copy2('/tmp/ARTICLE_SMITA_GFR_Correlations.xlsx', '/home/daytona/workspace/smita-gfr/ARTICLE_SMITA_GFR_Correlations.xlsx') print('Copied') " && ls -la /home/daytona/workspace/smita-gfr/

python3 -c " import shutil, os os.makedirs('/home/daytona/workspace/smita-gfr', exist_ok=True) shutil.copy('/tmp/ARTICLE_SMITA_GFR_Correlations.xlsx', '/home/daytona/workspace/smita-gfr/ARTICLE_SMITA_GFR_Correlations.xlsx') print('Copied OK') " && ls -la /home/daytona/workspace/smita-gfr/

python3 -c " import shutil, os os.makedirs('/home/daytona/workspace/smita-gfr', exist_ok=True) # Use copyfileobj directly with open('/tmp/ARTICLE_SMITA_GFR_Correlations.xlsx','rb') as src, open('/home/daytona/workspace/smita-gfr/ARTICLE_SMITA_GFR_Correlations.xlsx','wb') as dst: dst.write(src.read()) print('Done') " && ls -lh /home/daytona/workspace/smita-gfr/

python3 << 'EOF' from scipy import stats import numpy as np import openpyxl wb_src = openpyxl.load_workbook('/home/daytona/workspace/attachments/44a34df6-ea90-4821-87a9-f59d396c13db/ARTICLE SMITA-updated GFR.xlsx') ws = wb_src['Male'] data = {k: [] for k in ['TC','TG','HDL','LDL','VLDL','TC_HDL','LDL_HDL','CYS_C','CREAT','eGFR_Creat','eGFR_CysC']} for row in ws.iter_rows(min_row=4, max_row=ws.max_row, values_only=True): if row[0] is None: continue age=row[3]; creat=row[5]; tc=row[6]; tg=row[7]; hdl=row[8] ldl=row[9]; vldl=row[10]; tc_hdl=row[11]; ldl_hdl=row[12]; cys_c=row[13]; sex=row[2] if sex=='Male': egfr_creat = 175*(creat**-1.154)*(age**-0.203) if (age and creat) else None egfr_cysc = 127.7*(cys_c**-1.17)*(age**-0.13) if (age and cys_c) else None else: egfr_creat = 175*(creat**-1.154)*(age**-0.203)*0.742 if (age and creat) else None egfr_cysc = 127.7*(cys_c**-1.17)*(age**-0.13)*0.91 if (age and cys_c) else None if all(v is not None for v in [tc,tg,hdl,ldl,vldl,tc_hdl,ldl_hdl,cys_c,creat,egfr_creat,egfr_cysc]): data['TC'].append(tc); data['TG'].append(tg); data['HDL'].append(hdl) data['LDL'].append(ldl); data['VLDL'].append(vldl) data['TC_HDL'].append(tc_hdl); data['LDL_HDL'].append(ldl_hdl) data['CYS_C'].append(cys_c); data['CREAT'].append(creat) data['eGFR_Creat'].append(egfr_creat); data['eGFR_CysC'].append(egfr_cysc) print(f"N = {len(data['TC'])}") print(f"eGFR(CysC) range: {min(data['eGFR_CysC']):.2f} - {max(data['eGFR_CysC']):.2f}") print(f"eGFR(Creat) range: {min(data['eGFR_Creat']):.2f} - {max(data['eGFR_Creat']):.2f}") params = ['TC','TG','HDL','LDL','VLDL','TC_HDL','LDL_HDL'] labels = ['TC','TG','HDL','LDL','VLDL','TC/HDL','LDL/HDL'] print() print(f"{'Param':<10} | {'r (CysC-eGFR)':>14} {'p (CysC)':>10} {'Sig':>16} | {'r (Creat-eGFR)':>16} {'p (Creat)':>10} {'Sig':>16}") print("-"*100) for p,lbl in zip(params,labels): x = np.array(data[p]) r1,p1 = stats.pearsonr(x, np.array(data['eGFR_CysC'])) r2,p2 = stats.pearsonr(x, np.array(data['eGFR_Creat'])) s1 = 'p<0.05 *' if p1<0.05 else 'NS' s2 = 'p<0.05 *' if p2<0.05 else 'NS' print(f"{lbl:<10} | {r1:>14.4f} {p1:>10.4f} {s1:>16} | {r2:>16.4f} {p2:>10.4f} {s2:>16}") EOF