All Customers Atualizado 2 Arion - All Customers.csv May 2026

print(f"\n✅ Updated file saved as: {output_filename}") (first 5 rows in CSV format): CustomerID,Name,Email,Phone,Status,LastUpdate 1001,Arion Silva,arion.silva@email.com,+351912345678,Active,2026-04-10 1002,Mariana Costa,mariana.c@email.com,+351923456789,Inactive,2026-04-11 1003,Rui Pereira,rui.pereira@email.com,+351934567890,Active,2026-04-12 1004,Ana Sousa,ana.sousa@email.com,+351945678901,Pending,2026-04-13 1005,João Lima,joao.lima@email.com,+351956789012,Active,2026-04-13 🧹 If you meant to clean/fix the CSV (remove duplicates, standardize columns): df_clean = df.drop_duplicates(subset=["CustomerID", "Email"]) df_clean.columns = df_clean.columns.str.strip().str.lower().str.replace(" ", "_") df_clean.to_csv("all_customers_cleaned.csv", index=False) Let me know which “piece” you actually need (code, sample, report, analysis, etc.), and I’ll refine the output exactly to your use case.

print("\nColumn names:") print(df.columns.tolist()) df["Update_Version"] = 2 df["Last_Update"] = pd.Timestamp.now().strftime("%Y-%m-%d %H:%M:%S") Save updated version output_filename = "all customers atualizado 3 arion - all customers.csv" df.to_csv(output_filename, index=False, encoding='utf-8-sig') all customers atualizado 2 arion - all customers.csv

Since I don’t have direct access to your local files, I’ll provide a that reads, updates, and processes a CSV file with a similar name pattern. This assumes the CSV contains customer data and you want to handle updates (e.g., “atualizado 2” meaning “updated 2” in Portuguese). 🐍 Python script to read and update the CSV import pandas as pd import os File path (adjust as needed) filename = "all customers atualizado 2 arion - all customers.csv" Check if file exists if not os.path.exists(filename): print(f"File not found: {filename}") exit() Read CSV df = pd.read_csv(filename, encoding='utf-8-sig') Display basic info print("✅ File loaded successfully!") print(f"Rows: {df.shape[0]}, Columns: {df.shape[1]}") print("\nFirst 5 rows:") print(df.head()) 🐍 Python script to read and update the