Linking Verizon Call Logs to Google Contacts Using Google Colab and Google Sheets

Linking Call Logs to Google Contacts Using Google Colab and Google Sheets**

Do you have a long list of call logs and want to match them with your contact names quickly? This guide will show you how I used Google Colab to clean up my contact list and then linked it with my call log in Google Sheets. Here’s how I automated it to save hours of tedious work.

The Goal: Match Call Logs with Google Contacts

The task seemed straightforward: link a Verizon call log with Google Contacts to see names next to each phone number. However, Google Contacts had phone numbers in various formats (e.g., with country codes, parentheses, and dashes), while the call log had plain 10-digit numbers. Here’s how I solved this using Google Colab and Google Sheets.

Step 1: Preparing the Data in Google Sheets

First, I uploaded my Verizon call log CSV file into Google Sheets. The CALL LOG sheet contained:

Number Called: the actual phone numbers for each call.
Date and Time: the date and time of each call.

Then, I exported my Google Contacts as a CSV and imported it as the CONTACTS sheet in Google Sheets. This included:

Phone 1 - Value: contact numbers in various formats.
Full Name: the contact names I wanted to link to the numbers in my call log.

Step 2: Cleaning Data in Google Colab

To ensure the phone numbers matched in both sheets, I used Google Colab to clean and format the contact numbers in a consistent, 10-digit format. Here’s how:

Setting Up Google Colab: Open a new Google Colab notebook and upload your Contacts CSV.
Importing Required Libraries:
- Use pandas for data manipulation.
Cleaning the Phone Numbers:
- Remove all non-numeric characters (like +, (, and -).
- Keep only the last 10 digits to align with the format used in the CALL LOG.

Code Example

import pandas as pd

# Load the Contacts CSV
contacts_df = pd.read_csv('/path/to/Contacts.csv')

# Clean and format phone numbers to 10-digit format
contacts_df['Formatted Phone'] = contacts_df['Phone 1 - Value'].astype(str) \
    .str.replace(r'\D', '', regex=True) \
    .str[-10:]

# Verify formatting
contacts_df[['Phone 1 - Value', 'Formatted Phone']].head()

# Save the cleaned data to a new CSV file
contacts_df.to_csv('/path/to/Cleaned_Contacts.csv', index=False)

This code removes any unwanted characters from the phone numbers and ensures they’re formatted in a consistent, 10-digit structure. Now, each phone number is ready to match with those in CALL LOG.

Step 3: Importing Cleaned Data into Google Sheets

After cleaning the data, I uploaded the new Cleaned_Contacts.csv file into Google Sheets. This version of CONTACTS now has a new column, Formatted Phone, which contains the cleaned, 10-digit phone numbers.

Step 4: Setting Up the Lookup Formula in Google Sheets

With the cleaned contacts ready, I set up the VLOOKUP formula to link phone numbers in the CALL LOG sheet to contact names in CONTACTS. Here’s the formula I used:

=IFERROR(VLOOKUP(F2, CONTACTS!A:D, 4, FALSE), "Unknown")

Formula Breakdown:

F2: The cell in CALL LOG with the phone number we want to look up.
CONTACTS!A:D: The range in the CONTACTS sheet that includes Formatted Phone in column A and Full Name in column D.
4: Returns the value from the fourth column, Full Name.
IFERROR(…, “Unknown”): Displays “Unknown” if no match is found.

Step 5: Troubleshooting and Final Adjustments

If the VLOOKUP formula doesn’t immediately work, double-check these:

Consistent Formatting: Ensure both CALL LOG and CONTACTS have 10-digit plain numbers in matching formats.
Formula Test: You can test if a number in F2 exists in CONTACTS by using MATCH:
```
=MATCH(F2, CONTACTS!A:A, 0)
```
This will return a row number if there’s a match, confirming that the lookup is set up correctly.

Result: An Automated Contact Matching System

With this setup, every phone number in CALL LOG that has a corresponding contact in CONTACTS now automatically displays the contact’s full name. No more manual cross-referencing—Google Sheets and Google Colab handle it all!

Key Takeaways

Consistency in Data Formatting: Standardizing formats across datasets is crucial for accurate lookups.
Google Colab for Data Cleaning: Using Colab allowed me to clean and format data efficiently without altering the original Google Sheets data.
Automating with VLOOKUP: Setting up a VLOOKUP formula in Google Sheets saves time on repetitive manual matching.

Conclusion

With a combination of Google Colab and Google Sheets, I transformed a potentially time-consuming task into a simple, automated process. This approach isn’t just for call logs—it can be adapted for any scenario where you need to match data across sheets with different formats.

If you’ve faced a similar challenge, give this method a try, and feel free to share your experience!