Download data: LOG file format

This is the file type in which Meadows stores the list of events that occurred during a task. It is a tab-delimited text file containing three columns: time, description, and variables associated with each event.

When to use LOG

LOG is ideal when you need to:

• Analyze the timing of participant actions during a task
• Track stimulus placements and movements over time
• Debug or understand participant behavior in detail
• Process event sequences programmatically

For other data types, use CSV for tabular data, JSON for hierarchical data, or MAT for numerical arrays.

Compatible data structures

LOG format is available for:

• Events structure — Timestamped list of actions during a task

Loading LOG data

SpreadsheetPythonR

One way to view the events is to open the log file in a spreadsheet application:

1. Open Microsoft Excel or Google Sheets.
2. Use File → Import or File → Open.
3. Select the .log file.
4. Choose Tab as the delimiter when prompted.

import pandas as pd
import json

# Load the log file (tab-delimited)
data = pd.read_csv('Meadows_myStudy_events.log', sep='\t', names=['time', 'name', 'variables'])

# Parse the variables column from JSON strings
data['variables'] = data['variables'].apply(json.loads)

# Display the first few rows
print(data.head())

# Load the log file (tab-delimited)
data <- read.delim('Meadows_myStudy_events.log', header = FALSE, 
                   col.names = c('time', 'name', 'variables'))

# Display the first few rows
head(data)

Read more about the contents of the log file on the page about events.