cd /tmp/workspace/attachments/334d67e1-8c1d-444d-9eb6-7bbe3c5c794e/ && python3 -c " import openpyxl import pandas as pd wb = openpyxl.load_workbook('BALANCE CORRELATION WITH PP ANDPS og.xlsx') print('Sheets:', wb.sheetnames) for sheet in wb.sheetnames: ws = wb[sheet] print(f'\n--- Sheet: {sheet} ---') print(f'Dimensions: {ws.dimensions}') print(f'Max row: {ws.max_row}, Max col: {ws.max_column}') # Print first 5 rows for i, row in enumerate(ws.iter_rows(values_only=True)): if i < 5: print(f'Row {i+1}: {row}') else: break "

python3 -c " import pandas as pd import numpy as np df = pd.read_excel('/tmp/workspace/attachments/334d67e1-8c1d-444d-9eb6-7bbe3c5c794e/BALANCE CORRELATION WITH PP ANDPS og.xlsx') print('Shape:', df.shape) print('Columns:', list(df.columns)) print() print(df.head(10).to_string()) print() print('Dtypes:') print(df.dtypes) print() print('Missing values:') print(df.isnull().sum()) "

python3 << 'PYEOF' import pandas as pd import numpy as np from scipy import stats import warnings warnings.filterwarnings('ignore') df = pd.read_excel('/tmp/workspace/attachments/334d67e1-8c1d-444d-9eb6-7bbe3c5c794e/BALANCE CORRELATION WITH PP ANDPS og.xlsx') # ── Gender encoding ────────────────────────────────────────────────────────── df['GENDER'] = df.apply(lambda r: 'Male' if r['MALE'] == 'M' else 'Female', axis=1) n_male = (df['GENDER'] == 'Male').sum() n_female = (df['GENDER'] == 'Female').sum() n_total = len(df) print("=== SAMPLE SIZE ===") print(f"Total N = {n_total}") print(f"Male = {n_male} ({n_male/n_total*100:.1f}%)") print(f"Female = {n_female} ({n_female/n_total*100:.1f}%)") # ── Numerical variables ─────────────────────────────────────────────────────── num_vars = [ 'AGE', 'SENSATION ON 1St METATARSAL','SENSATION ON HEEL','TOTAL SENSITIVITY', 'PLANTAR PRESSURE OF RIGHT FOREFOOT','PLANTAR PRESSURE OF LEFT FOREFOOT', 'PLANTAR PRESSURE OF RIGHT HINDFOOT','PLANTAR PRESSURE OF LEFT HINDFOOT', 'MAXIMUM PLANTAR PRESSURE ON RIGHT FOOT','MAXIMUM PLANTAR PRESSURE ON LEFTFOOT', 'MINIBESTEST SCORE','ANTICIPATORY','REACTIVE POSTURAL CONTROL', 'SENSORY ORIENTATION','DYNAMIC GAIT' ] print("\n=== DESCRIPTIVE STATISTICS ===") desc = df[num_vars].agg(['mean','std','min','max','median']) print(desc.round(3).to_string()) print("\n=== NORMALITY TEST (Shapiro-Wilk) ===") normality = {} for v in num_vars: stat, p = stats.shapiro(df[v].dropna()) normality[v] = {'W': round(stat,4), 'p': round(p,4), 'Normal': 'Yes' if p > 0.05 else 'No'} print(f"{v:50s} W={stat:.4f} p={p:.4f} {'Normal' if p>0.05 else 'NOT Normal'}") # ── Correlation variables ──────────────────────────────────────────────────── # Balance = MiniBESTest total + subscores # Plantar Pressure vars # Plantar Sensation vars balance_vars = ['MINIBESTEST SCORE','ANTICIPATORY','REACTIVE POSTURAL CONTROL', 'SENSORY ORIENTATION','DYNAMIC GAIT'] pp_vars = ['PLANTAR PRESSURE OF RIGHT FOREFOOT','PLANTAR PRESSURE OF LEFT FOREFOOT', 'PLANTAR PRESSURE OF RIGHT HINDFOOT','PLANTAR PRESSURE OF LEFT HINDFOOT', 'MAXIMUM PLANTAR PRESSURE ON RIGHT FOOT','MAXIMUM PLANTAR PRESSURE ON LEFTFOOT'] sensation_vars = ['SENSATION ON 1St METATARSAL','SENSATION ON HEEL','TOTAL SENSITIVITY'] print("\n=== PEARSON CORRELATION: BALANCE vs PLANTAR PRESSURE ===") print(f"{'Plantar Pressure Var':<42} {'Balance Var':<28} r p-value Sig") print("-"*115) pp_balance_results = [] for bv in balance_vars: for pv in pp_vars: r, p = stats.pearsonr(df[pv], df[bv]) sig = '**' if p < 0.01 else ('*' if p < 0.05 else 'ns') pp_balance_results.append({'Plantar Pressure': pv, 'Balance': bv, 'r': round(r,4), 'p': round(p,4), 'Sig': sig}) print(f"{pv:<42} {bv:<28} {r:+.4f} {p:.4f} {sig}") print("\n=== PEARSON CORRELATION: BALANCE vs PLANTAR SENSATION ===") print(f"{'Plantar Sensation Var':<32} {'Balance Var':<28} r p-value Sig") print("-"*100) ps_balance_results = [] for bv in balance_vars: for sv in sensation_vars: r, p = stats.pearsonr(df[sv], df[bv]) sig = '**' if p < 0.01 else ('*' if p < 0.05 else 'ns') ps_balance_results.append({'Plantar Sensation': sv, 'Balance': bv, 'r': round(r,4), 'p': round(p,4), 'Sig': sig}) print(f"{sv:<32} {bv:<28} {r:+.4f} {p:.4f} {sig}") print("\n=== PEARSON CORRELATION: PLANTAR PRESSURE vs PLANTAR SENSATION ===") print(f"{'Plantar Pressure Var':<42} {'Sensation Var':<32} r p-value Sig") print("-"*115) pp_ps_results = [] for sv in sensation_vars: for pv in pp_vars: r, p = stats.pearsonr(df[pv], df[sv]) sig = '**' if p < 0.01 else ('*' if p < 0.05 else 'ns') pp_ps_results.append({'Plantar Pressure': pv, 'Plantar Sensation': sv, 'r': round(r,4), 'p': round(p,4), 'Sig': sig}) print(f"{pv:<42} {sv:<32} {r:+.4f} {p:.4f} {sig}") PYEOF

mkdir -p /tmp/workspace/balance_correlation_study && python3 << 'PYEOF' import pandas as pd import numpy as np from scipy import stats import openpyxl from openpyxl.styles import (Font, PatternFill, Alignment, Border, Side, GradientFill) from openpyxl.utils import get_column_letter from openpyxl.styles.numbers import FORMAT_NUMBER_00 import warnings warnings.filterwarnings('ignore') # ──────────────────────────────────────────────────────────────────────────── # 1. LOAD DATA # ──────────────────────────────────────────────────────────────────────────── df = pd.read_excel('/tmp/workspace/attachments/334d67e1-8c1d-444d-9eb6-7bbe3c5c794e/BALANCE CORRELATION WITH PP ANDPS og.xlsx') df['GENDER'] = df.apply(lambda r: 'Male' if r['MALE'] == 'M' else 'Female', axis=1) n_total = len(df) n_male = (df['GENDER'] == 'Male').sum() n_female = (df['GENDER'] == 'Female').sum() num_vars = [ 'AGE', 'SENSATION ON 1St METATARSAL','SENSATION ON HEEL','TOTAL SENSITIVITY', 'PLANTAR PRESSURE OF RIGHT FOREFOOT','PLANTAR PRESSURE OF LEFT FOREFOOT', 'PLANTAR PRESSURE OF RIGHT HINDFOOT','PLANTAR PRESSURE OF LEFT HINDFOOT', 'MAXIMUM PLANTAR PRESSURE ON RIGHT FOOT','MAXIMUM PLANTAR PRESSURE ON LEFTFOOT', 'MINIBESTEST SCORE','ANTICIPATORY','REACTIVE POSTURAL CONTROL', 'SENSORY ORIENTATION','DYNAMIC GAIT' ] balance_vars = ['MINIBESTEST SCORE','ANTICIPATORY','REACTIVE POSTURAL CONTROL', 'SENSORY ORIENTATION','DYNAMIC GAIT'] pp_vars = ['PLANTAR PRESSURE OF RIGHT FOREFOOT','PLANTAR PRESSURE OF LEFT FOREFOOT', 'PLANTAR PRESSURE OF RIGHT HINDFOOT','PLANTAR PRESSURE OF LEFT HINDFOOT', 'MAXIMUM PLANTAR PRESSURE ON RIGHT FOOT','MAXIMUM PLANTAR PRESSURE ON LEFTFOOT'] sensation_vars = ['SENSATION ON 1St METATARSAL','SENSATION ON HEEL','TOTAL SENSITIVITY'] # ──────────────────────────────────────────────────────────────────────────── # 2. COMPUTE STATISTICS # ──────────────────────────────────────────────────────────────────────────── # Descriptive desc = {} for v in num_vars: s = df[v].dropna() desc[v] = {'Mean': round(s.mean(),2), 'SD': round(s.std(),2), 'Min': round(s.min(),2), 'Max': round(s.max(),2), 'Median': round(s.median(),2)} # Shapiro-Wilk normality = {} for v in num_vars: W, p = stats.shapiro(df[v].dropna()) normality[v] = {'W': round(W,4), 'p': round(p,4), 'Normal': 'Yes (p>0.05)' if p > 0.05 else 'No (p<0.05)'} # Correlation helper def pearson(a, b): r, p = stats.pearsonr(df[a], df[b]) sig = '** (p<0.01)' if p < 0.01 else ('* (p<0.05)' if p < 0.05 else 'ns') return round(r,4), round(p,4), sig # ──────────────────────────────────────────────────────────────────────────── # 3. STYLE HELPERS # ──────────────────────────────────────────────────────────────────────────── TITLE_FILL = PatternFill('solid', fgColor='1F3864') # dark navy HEADER_FILL = PatternFill('solid', fgColor='2E75B6') # blue SUBHEAD_FILL = PatternFill('solid', fgColor='D6E4F0') # light blue SIG_FILL = PatternFill('solid', fgColor='E2EFDA') # green tint NS_FILL = PatternFill('solid', fgColor='FFFFFF') ALT_FILL = PatternFill('solid', fgColor='F2F7FB') RED_FILL = PatternFill('solid', fgColor='FCE4D6') # slight red for NOT normal def title_font(sz=14, bold=True): return Font(name='Arial', size=sz, bold=bold, color='FFFFFF') def header_font(sz=11, bold=True): return Font(name='Arial', size=sz, bold=bold, color='FFFFFF') def body_font(sz=10, bold=False, color='000000'): return Font(name='Arial', size=sz, bold=bold, color=color) def thin_border(): s = Side(style='thin', color='B8CCE4') return Border(left=s, right=s, top=s, bottom=s) def center(): return Alignment(horizontal='center', vertical='center', wrap_text=True) def left(): return Alignment(horizontal='left', vertical='center', wrap_text=True) def style_title(ws, row, col, value, colspan=1): cell = ws.cell(row=row, column=col, value=value) cell.font = title_font() cell.fill = TITLE_FILL cell.alignment = center() cell.border = thin_border() if colspan > 1: ws.merge_cells(start_row=row, start_column=col, end_row=row, end_column=col+colspan-1) return cell def style_header(ws, row, col, value, colspan=1): cell = ws.cell(row=row, column=col, value=value) cell.font = header_font() cell.fill = HEADER_FILL cell.alignment = center() cell.border = thin_border() if colspan > 1: ws.merge_cells(start_row=row, start_column=col, end_row=row, end_column=col+colspan-1) return cell def style_subhead(ws, row, col, value): cell = ws.cell(row=row, column=col, value=value) cell.font = Font(name='Arial', size=10, bold=True, color='1F3864') cell.fill = SUBHEAD_FILL cell.alignment = center() cell.border = thin_border() return cell def write_cell(ws, row, col, value, bold=False, fill=None, align='center', color='000000'): cell = ws.cell(row=row, column=col, value=value) cell.font = body_font(bold=bold, color=color) cell.fill = fill if fill else NS_FILL cell.alignment = center() if align == 'center' else left() cell.border = thin_border() return cell # ════════════════════════════════════════════════════════════════════════════ # 4. CREATE WORKBOOK # ════════════════════════════════════════════════════════════════════════════ wb = openpyxl.Workbook() # ────────────────────────────────────────────────────────────────────────── # SHEET 1 – COVER / SUMMARY # ────────────────────────────────────────────────────────────────────────── ws1 = wb.active ws1.title = 'Study Overview' ws1.sheet_view.showGridLines = False ws1.column_dimensions['A'].width = 5 ws1.column_dimensions['B'].width = 38 ws1.column_dimensions['C'].width = 22 style_title(ws1, 1, 2, 'CORRELATION / BALANCE WITH PLANTAR PRESSURE & PLANTAR SENSATION', colspan=2) ws1.row_dimensions[1].height = 36 style_title(ws1, 2, 2, 'In Community-Dwelling Elderly Individuals', colspan=2) ws1.row_dimensions[2].height = 22 ws1.cell(row=3, column=2).value = '' row = 4 style_header(ws1, row, 2, 'STUDY DETAILS', colspan=2); row+=1 details = [ ('Study Design', 'Cross-sectional Observational Study'), ('Population', 'Community-Dwelling Elderly Individuals'), ('Total Sample Size (N)', str(n_total)), ('Males', f'{n_male} ({n_male/n_total*100:.1f}%)'), ('Females', f'{n_female} ({n_female/n_total*100:.1f}%)'), ('Outcome 1 – Balance', 'MiniBESTest (Total + 4 Subscores)'), ('Outcome 2 – Plantar Pressure', '6 variables (Forefoot/Hindfoot, R/L, Max)'), ('Outcome 3 – Plantar Sensation', 'Sensation @ 1st Metatarsal, Heel, Total'), ('Statistical Software', 'Python SciPy (SPSS-equivalent outputs)'), ('Normality Test', 'Shapiro-Wilk Test'), ('Correlation Test', 'Pearson Correlation Coefficient (r)'), ('Significance Level', 'α = 0.05 | ** p<0.01 | * p<0.05 | ns = not significant'), ] for k, v in details: alt = ALT_FILL if row % 2 == 0 else NS_FILL write_cell(ws1, row, 2, k, bold=True, fill=SUBHEAD_FILL, align='left') write_cell(ws1, row, 3, v, fill=alt, align='left') row += 1 ws1.row_dimensions[row].height = 14 row += 1 style_header(ws1, row, 2, 'SHEETS IN THIS WORKBOOK', colspan=2); row+=1 sheets = [ ('Study Overview', 'This sheet – study details and legend'), ('1. Descriptive Stats', 'Mean, SD, Min, Max, Median for all variables'), ('2. Normality Test', 'Shapiro-Wilk W and p-value for all numerical vars'), ('3. Gender Frequency', 'Frequency and % of categorical variable (Gender)'), ('4. Corr PP vs Balance','Pearson r – Plantar Pressure vs Balance (MiniBESTest)'), ('5. Corr PS vs Balance','Pearson r – Plantar Sensation vs Balance'), ('6. Corr PP vs PS', 'Pearson r – Plantar Pressure vs Plantar Sensation'), ('7. Corr Matrix', 'Full correlation matrix (heatmap-style)'), ] for nm, desc_s in sheets: alt = ALT_FILL if row % 2 == 0 else NS_FILL write_cell(ws1, row, 2, nm, bold=True, fill=SUBHEAD_FILL, align='left') write_cell(ws1, row, 3, desc_s, fill=alt, align='left') row += 1 # ────────────────────────────────────────────────────────────────────────── # SHEET 2 – DESCRIPTIVE STATISTICS # ────────────────────────────────────────────────────────────────────────── ws2 = wb.create_sheet('1. Descriptive Stats') ws2.sheet_view.showGridLines = False col_widths2 = [5, 42, 12, 12, 12, 12, 12, 20] for i, w in enumerate(col_widths2, 1): ws2.column_dimensions[get_column_letter(i)].width = w style_title(ws2, 1, 2, 'TABLE 1 – DESCRIPTIVE STATISTICS', colspan=7) ws2.row_dimensions[1].height = 30 style_header(ws2, 2, 2, 'Variable'); style_header(ws2, 2, 3, 'Mean') style_header(ws2, 2, 4, 'SD'); style_header(ws2, 2, 5, 'Median') style_header(ws2, 2, 6, 'Min'); style_header(ws2, 2, 7, 'Max') style_header(ws2, 2, 8, 'Normality (S-W)') sections = [ ('DEMOGRAPHIC', ['AGE']), ('PLANTAR SENSATION', sensation_vars), ('PLANTAR PRESSURE', pp_vars), ('BALANCE (MiniBESTest)', balance_vars), ] r = 3 for sec_name, vars_list in sections: ws2.merge_cells(start_row=r, start_column=2, end_row=r, end_column=8) c = ws2.cell(row=r, column=2, value=sec_name) c.font = Font(name='Arial', size=10, bold=True, color='1F3864') c.fill = SUBHEAD_FILL c.alignment = left(); c.border = thin_border() r += 1 for v in vars_list: d = desc[v] nm = normality[v] alt = ALT_FILL if r % 2 == 0 else NS_FILL norm_fill = NS_FILL if 'Yes' in nm['Normal'] else RED_FILL write_cell(ws2, r, 2, v, align='left', fill=alt) write_cell(ws2, r, 3, d['Mean'], fill=alt) write_cell(ws2, r, 4, d['SD'], fill=alt) write_cell(ws2, r, 5, d['Median'], fill=alt) write_cell(ws2, r, 6, d['Min'], fill=alt) write_cell(ws2, r, 7, d['Max'], fill=alt) write_cell(ws2, r, 8, nm['Normal'], fill=norm_fill) r += 1 r += 1 ws2.cell(row=r, column=2, value='Note: Normality assessed by Shapiro-Wilk test. Red = non-normal distribution (p<0.05).').font = Font(name='Arial', size=9, italic=True, color='595959') # ────────────────────────────────────────────────────────────────────────── # SHEET 3 – NORMALITY TEST # ────────────────────────────────────────────────────────────────────────── ws3 = wb.create_sheet('2. Normality Test') ws3.sheet_view.showGridLines = False for i, w in enumerate([5, 42, 12, 12, 22], 1): ws3.column_dimensions[get_column_letter(i)].width = w style_title(ws3, 1, 2, 'TABLE 2 – NORMALITY TEST (SHAPIRO-WILK)', colspan=4) ws3.row_dimensions[1].height = 30 style_header(ws3, 2, 2, 'Variable') style_header(ws3, 2, 3, 'W Statistic') style_header(ws3, 2, 4, 'p-value') style_header(ws3, 2, 5, 'Normal Distribution?') r = 3 for v in num_vars: nm = normality[v] alt = ALT_FILL if r % 2 == 0 else NS_FILL norm_fill = NS_FILL if 'Yes' in nm['Normal'] else RED_FILL write_cell(ws3, r, 2, v, align='left', fill=alt) write_cell(ws3, r, 3, nm['W'], fill=alt) write_cell(ws3, r, 4, nm['p'], fill=alt) write_cell(ws3, r, 5, nm['Normal'], fill=norm_fill) r += 1 r += 1 n = ws3.cell(row=r, column=2, value='Note: p > 0.05 = data is normally distributed. p < 0.05 = non-normal (Pearson r still reported as commonly used in clinical research).') n.font = Font(name='Arial', size=9, italic=True, color='595959') # ────────────────────────────────────────────────────────────────────────── # SHEET 4 – GENDER FREQUENCY # ────────────────────────────────────────────────────────────────────────── ws4 = wb.create_sheet('3. Gender Frequency') ws4.sheet_view.showGridLines = False for i, w in enumerate([5, 22, 14, 14], 1): ws4.column_dimensions[get_column_letter(i)].width = w style_title(ws4, 1, 2, 'TABLE 3 – GENDER FREQUENCY', colspan=3) ws4.row_dimensions[1].height = 28 style_header(ws4, 2, 2, 'Gender') style_header(ws4, 2, 3, 'Frequency (n)') style_header(ws4, 2, 4, 'Percentage (%)') rows_g = [('Male', n_male, f'{n_male/n_total*100:.1f}'), ('Female', n_female, f'{n_female/n_total*100:.1f}'), ('Total', n_total, '100.0')] for i, (g, n_g, pct) in enumerate(rows_g, 3): alt = ALT_FILL if i % 2 == 0 else NS_FILL write_cell(ws4, i, 2, g, bold=(g=='Total'), align='left', fill=alt) write_cell(ws4, i, 3, n_g, bold=(g=='Total'), fill=alt) write_cell(ws4, i, 4, pct, bold=(g=='Total'), fill=alt) # ────────────────────────────────────────────────────────────────────────── # HELPER: write a correlation table # ────────────────────────────────────────────────────────────────────────── def write_corr_sheet(ws, title, row_vars, col_vars, row_label, col_label): ws.sheet_view.showGridLines = False base_w = 30 ws.column_dimensions['A'].width = 4 ws.column_dimensions['B'].width = 38 for ci, cv in enumerate(col_vars, 3): ws.column_dimensions[get_column_letter(ci)].width = 20 style_title(ws, 1, 2, title, colspan=2 + len(col_vars) - 1) ws.row_dimensions[1].height = 30 # Column headers style_subhead(ws, 2, 2, row_label + ' \\ ' + col_label) for ci, cv in enumerate(col_vars, 3): style_header(ws, 2, ci, cv) r = 3 for rv in row_vars: alt = ALT_FILL if r % 2 == 0 else NS_FILL write_cell(ws, r, 2, rv, bold=True, align='left', fill=SUBHEAD_FILL) for ci, cv in enumerate(col_vars, 3): rval, pval, sig = pearson(rv, cv) label = f'r = {rval}\np = {pval}\n{sig}' if '**' in sig: fill = PatternFill('solid', fgColor='C6EFCE') elif '*' in sig: fill = PatternFill('solid', fgColor='FFEB9C') else: fill = alt cell = ws.cell(row=r, column=ci, value=label) cell.font = body_font(sz=9, bold=('**' in sig or ('*' in sig and '**' not in sig))) cell.fill = fill cell.alignment = center() cell.border = thin_border() r += 1 r += 1 ws.cell(row=r, column=2, value='** p<0.01 (green) * p<0.05 (yellow) ns = not significant').font = Font(name='Arial', size=9, italic=True, color='595959') ws.row_dimensions[r].height = 14 # ────────────────────────────────────────────────────────────────────────── # SHEET 5 – PP vs BALANCE # ────────────────────────────────────────────────────────────────────────── ws5 = wb.create_sheet('4. Corr PP vs Balance') write_corr_sheet(ws5, 'TABLE 4 – PEARSON CORRELATION: PLANTAR PRESSURE vs BALANCE (MiniBESTest)', pp_vars, balance_vars, 'Plantar Pressure', 'Balance Score') # ────────────────────────────────────────────────────────────────────────── # SHEET 6 – SENSATION vs BALANCE # ────────────────────────────────────────────────────────────────────────── ws6 = wb.create_sheet('5. Corr PS vs Balance') write_corr_sheet(ws6, 'TABLE 5 – PEARSON CORRELATION: PLANTAR SENSATION vs BALANCE', sensation_vars, balance_vars, 'Plantar Sensation', 'Balance Score') # ────────────────────────────────────────────────────────────────────────── # SHEET 7 – PP vs SENSATION # ────────────────────────────────────────────────────────────────────────── ws7 = wb.create_sheet('6. Corr PP vs PS') write_corr_sheet(ws7, 'TABLE 6 – PEARSON CORRELATION: PLANTAR PRESSURE vs PLANTAR SENSATION', pp_vars, sensation_vars, 'Plantar Pressure', 'Plantar Sensation') # ────────────────────────────────────────────────────────────────────────── # SHEET 8 – FULL CORRELATION MATRIX # ────────────────────────────────────────────────────────────────────────── ws8 = wb.create_sheet('7. Corr Matrix') ws8.sheet_view.showGridLines = False all_corr_vars = sensation_vars + pp_vars + balance_vars style_title(ws8, 1, 2, 'TABLE 7 – FULL PEARSON CORRELATION MATRIX', colspan=len(all_corr_vars)+1) ws8.row_dimensions[1].height = 28 ws8.column_dimensions['A'].width = 3 ws8.column_dimensions['B'].width = 38 for ci in range(3, 3+len(all_corr_vars)): ws8.column_dimensions[get_column_letter(ci)].width = 16 # Headers style_subhead(ws8, 2, 2, 'Variable') for ci, v in enumerate(all_corr_vars, 3): style_header(ws8, 2, ci, v) for ri, rv in enumerate(all_corr_vars, 3): alt = ALT_FILL if ri % 2 == 0 else NS_FILL write_cell(ws8, ri, 2, rv, bold=True, align='left', fill=SUBHEAD_FILL) for ci, cv in enumerate(all_corr_vars, 3): if rv == cv: cell = ws8.cell(row=ri, column=ci, value='1.000') cell.font = Font(name='Arial', size=9, bold=True) cell.fill = PatternFill('solid', fgColor='D9D9D9') cell.alignment = center() cell.border = thin_border() else: rval, pval, sig = pearson(rv, cv) if '**' in sig: fill = PatternFill('solid', fgColor='C6EFCE') elif '*' in sig: fill = PatternFill('solid', fgColor='FFEB9C') else: fill = alt label = f'r={rval}\np={pval}\n{sig}' cell = ws8.cell(row=ri, column=ci, value=label) cell.font = Font(name='Arial', size=8, bold=('**' in sig)) cell.fill = fill cell.alignment = center() cell.border = thin_border() ws8.row_dimensions[ri].height = 40 r_note = 3 + len(all_corr_vars) + 1 ws8.cell(row=r_note, column=2, value='Green = ** p<0.01 | Yellow = * p<0.05 | White/Alt = ns | Grey = self-correlation').font = Font(name='Arial', size=9, italic=True, color='595959') # ────────────────────────────────────────────────────────────────────────── # SAVE # ────────────────────────────────────────────────────────────────────────── out_path = '/tmp/workspace/balance_correlation_study/Statistical_Analysis_Results.xlsx' wb.save(out_path) print(f'Saved to: {out_path}') PYEOF

ls -lh /tmp/workspace/balance_correlation_study/