WhatsApp Chat to Excel Converter for Tree Surveys

Overview

This project provides a tool for converting WhatsApp chat data into structured Excel files, specifically tailored for tree surveys. It is designed to organize data about tree species, their heights, and trunk measurements. The entire project is contained in an IPython Notebook (ipynb), making it versatile and user-friendly. You can run it in various environments that support IPython notebooks, such as Google Colab, Anaconda, or Jupyter Notebook. This flexibility allows for easy execution and adaptation of the tool in different settings, catering to a wide range of user preferences and technical setups.

How to Use

1. Create a WhatsApp Group: For example, a group named "Medidas".

2. Mark Each Segment: Use identifiers like P1, P2, etc., to denote different segments.

3. Record Data: Enter the name of the tree species, its measurements, and height.

4. Export Chat:

   • Open chat options (three dots).
   • Click on "More".
   • Select "Export chat".
   • Choose to export without media.
   • Share the exported chat file back to the same chat.
   • Download and upload the file to this platform (see instructions below).

5. Prepare the Data:

   • Copy this page to your drive for editing.
   • Delete the example file 'WhatsApp Chat with Medidas.txt' from the folder on the left.
   • Upload your exported chat conversation.

6. Run the Code:

   • Modify the file name in the first line of the code to match the name of your uploaded file.
   • Execute the script by pressing Ctrl + F9.

7. Download the Processed File:

   • Refresh the page.
   • Download the 'medidas_segmentadas.xlsx' file.

Processing Steps

• The script reads the exported WhatsApp chat.
• It identifies and segregates data based on predefined patterns (like P1, P2, etc.).
• Tree species, measurements, and heights are extracted and organized.
• Irrelevant messages (like "deleted" or "apagou") are filtered out.
• Data is structured into a DataFrame, with columns for species, height, number of measurements, and individual measurements.
• Each segment (e.g., P1, P2) is saved as a separate CSV file and as a sheet in an Excel file.

Example Code Snippet

# Import necessary libraries
import re
import pandas as pd
from collections import defaultdict

# Function to process the content of the chat file
def process_content(content):
    data_dict = defaultdict(list)
    current_segment = None
    current_species = None
    current_height = None
    measures = []

    # Regular expressions to identify segments, species, measurements, and heights
    segment_pattern = re.compile(r"\d{2}/\d{2}/\d{2}, \d{2}:\d{2} - .+: P\d+")
    species_pattern = re.compile(r"^\d{2}/\d{2}/\d{2}, \d{2}:\d{2} - .+: (.+)$")
    measure_pattern = re.compile(r"^(\d+(?:,\d+)?)\n$")
    height_pattern = re.compile(r"^(\d+m)\n$")
    
    # Process each line of the chat
    for line in content:
        if segment_pattern.match(line):
            if current_segment and current_species:
                data_dict[current_segment].append([current_species, current_height, len(measures)] + measures)
            current_segment = line.strip().split()[-1]
            current_species = None
            current_height = None
            measures = []
        elif species_pattern.match(line):
            if current_species:
                data_dict[current_segment].append([current_species, current_height, len(measures)] + measures)
            current_species = species_pattern.match(line).group(1)
            measures = []
        elif height_pattern.match(line):
            current_height = height_pattern.match(line).group(1)
        elif measure_pattern.match(line):
            measures.append(measure_pattern.match(line).group(1))

    if current_species:
        data_dict[current_segment].append([current_species, current_height, len(measures)] + measures)

    return data_dict

# Example: Reading and processing the chat file
file_path = 'WhatsApp Chat with Medidas.txt'
with open(file_path, 'r') as file:
    content = file.readlines()

data_dict = process_content(content)

# Creating DataFrames and exporting to CSV and XLSX files
# ...

Output

The tool outputs CSV files for each segment and an Excel file with each segment as a separate sheet, providing a structured format for tree survey data extracted from WhatsApp chats.