updating daily miror
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ske087
BIN
Open .Orders WIZ New.xlsb
Normal file
BIN
Open .Orders WIZ New.xlsb
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185
view_dashboard.py
Executable file
185
view_dashboard.py
Executable file
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#!/usr/bin/env python3
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"""
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Excel Dashboard Viewer
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Reads and displays the Dashboard sheet from Open .Orders WIZ New.xlsb
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"""
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import pandas as pd
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import sys
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import os
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def view_dashboard(file_path):
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"""View the Dashboard sheet from the Excel file"""
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if not os.path.exists(file_path):
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print(f"❌ File not found: {file_path}")
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return
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try:
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print("=" * 80)
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print(f"📊 Loading Excel file: {os.path.basename(file_path)}")
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print("=" * 80)
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# First, list all sheets in the file
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print("\n📋 Available sheets:")
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xls = pd.ExcelFile(file_path, engine='pyxlsb')
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for i, sheet in enumerate(xls.sheet_names, 1):
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print(f" {i}. {sheet}")
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# Try to find and read Daily Mirror sheet
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dashboard_sheet = None
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for sheet in xls.sheet_names:
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if 'daily mirror' in sheet.lower() or 'dashboard' in sheet.lower() or 'dash' in sheet.lower():
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dashboard_sheet = sheet
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break
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if not dashboard_sheet:
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print("\n⚠️ No 'Dashboard' sheet found. Available sheets listed above.")
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print("\nPlease select a sheet to view (enter number or name):")
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choice = input("> ").strip()
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if choice.isdigit():
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idx = int(choice) - 1
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if 0 <= idx < len(xls.sheet_names):
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dashboard_sheet = xls.sheet_names[idx]
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else:
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if choice in xls.sheet_names:
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dashboard_sheet = choice
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if not dashboard_sheet:
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print("❌ Invalid selection")
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return
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print(f"\n📊 Reading sheet: {dashboard_sheet}")
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print("=" * 80)
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# Read the sheet
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df = pd.read_excel(file_path, sheet_name=dashboard_sheet, engine='pyxlsb')
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# Display basic info
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print(f"\n📏 Sheet dimensions: {df.shape[0]} rows × {df.shape[1]} columns")
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print(f"\n📋 Column names:")
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for i, col in enumerate(df.columns, 1):
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print(f" {i}. {col}")
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# Display first few rows
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print(f"\n📊 First 10 rows:")
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print("-" * 80)
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pd.set_option('display.max_columns', None)
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pd.set_option('display.width', None)
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pd.set_option('display.max_colwidth', 50)
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print(df.head(10).to_string())
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# Display data types
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print(f"\n📝 Data types:")
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print(df.dtypes)
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# Display summary statistics for numeric columns
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numeric_cols = df.select_dtypes(include=['number']).columns
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if len(numeric_cols) > 0:
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print(f"\n📈 Summary statistics (numeric columns):")
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print(df[numeric_cols].describe())
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# Check for date columns
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date_cols = []
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for col in df.columns:
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if 'date' in col.lower():
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date_cols.append(col)
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if date_cols:
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print(f"\n📅 Date columns found: {', '.join(date_cols)}")
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for col in date_cols:
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try:
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df[col] = pd.to_datetime(df[col], errors='coerce')
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print(f" {col}: {df[col].min()} to {df[col].max()}")
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except:
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pass
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# Interactive menu
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while True:
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print("\n" + "=" * 80)
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print("📋 Options:")
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print(" 1. View more rows")
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print(" 2. Filter data")
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print(" 3. View specific columns")
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print(" 4. Export to CSV")
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print(" 5. View another sheet")
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print(" 6. Exit")
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print("=" * 80)
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choice = input("Select option (1-6): ").strip()
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if choice == '1':
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n = input("How many rows to display? (default 20): ").strip()
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n = int(n) if n.isdigit() else 20
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print(df.head(n).to_string())
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elif choice == '2':
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print(f"Available columns: {', '.join(df.columns)}")
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col = input("Enter column name to filter: ").strip()
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if col in df.columns:
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print(f"Unique values in {col}:")
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print(df[col].value_counts().head(20))
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val = input(f"Enter value to filter {col}: ").strip()
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filtered = df[df[col].astype(str).str.contains(val, case=False, na=False)]
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print(f"\nFiltered results ({len(filtered)} rows):")
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print(filtered.to_string())
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else:
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print("❌ Column not found")
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elif choice == '3':
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print(f"Available columns: {', '.join(df.columns)}")
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cols = input("Enter column names (comma-separated): ").strip()
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col_list = [c.strip() for c in cols.split(',')]
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valid_cols = [c for c in col_list if c in df.columns]
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if valid_cols:
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print(df[valid_cols].head(20).to_string())
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else:
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print("❌ No valid columns found")
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elif choice == '4':
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output_file = input("Enter output filename (default: dashboard_export.csv): ").strip()
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output_file = output_file if output_file else "dashboard_export.csv"
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df.to_csv(output_file, index=False)
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print(f"✅ Exported to {output_file}")
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elif choice == '5':
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print("\n📋 Available sheets:")
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for i, sheet in enumerate(xls.sheet_names, 1):
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print(f" {i}. {sheet}")
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sheet_choice = input("Select sheet (number or name): ").strip()
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if sheet_choice.isdigit():
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idx = int(sheet_choice) - 1
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if 0 <= idx < len(xls.sheet_names):
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dashboard_sheet = xls.sheet_names[idx]
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df = pd.read_excel(file_path, sheet_name=dashboard_sheet, engine='pyxlsb')
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print(f"\n📊 Loaded sheet: {dashboard_sheet}")
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print(f"Dimensions: {df.shape[0]} rows × {df.shape[1]} columns")
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print(df.head(10).to_string())
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else:
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if sheet_choice in xls.sheet_names:
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df = pd.read_excel(file_path, sheet_name=sheet_choice, engine='pyxlsb')
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print(f"\n📊 Loaded sheet: {sheet_choice}")
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print(f"Dimensions: {df.shape[0]} rows × {df.shape[1]} columns")
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print(df.head(10).to_string())
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elif choice == '6':
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print("👋 Goodbye!")
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break
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else:
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print("❌ Invalid option")
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except Exception as e:
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print(f"❌ Error reading file: {e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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file_path = "/srv/quality_app/Open .Orders WIZ New.xlsb"
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if len(sys.argv) > 1:
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file_path = sys.argv[1]
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view_dashboard(file_path)
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