https://github.com/niklasvonm/daylio

R Shiny app for analysis and visualization of Daylio data diaries
https://github.com/niklasvonm/daylio

Last synced: 8 days ago
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R Shiny app for analysis and visualization of Daylio data diaries

• Host: GitHub
• URL: https://github.com/niklasvonm/daylio
• Owner: NiklasvonM
• License: mit
• Created: 2021-01-30T12:26:00.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2024-08-18T19:45:34.000Z (3 months ago)
• Last Synced: 2024-10-15T03:29:01.463Z (22 days ago)
• Language: R
• Homepage:
• Size: 938 KB
• Stars: 7
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Daylio

This repository contains a Shiny dashboard with the purpose of data analysis and visualization for data collected with the app [Daylio](https://daylio.net/).

## Getting Started

- In case you do not bring your own data, skip this step and use the provided mock data. Otherwise export your data from the Daylio app to the folder ./data.

- Copy config_template.yaml and rename it config.yaml.

- Edit the file name of your data in config.yaml. Do not specify the path or the .csv file extension. Note that the data needs to be in the exact format from the Daylio app: It must contain the columns `full_date`, `weekday`, `mood`, `activities` which contains all the activities for the day, separated by " | ", and `note`. Other columns are ignored.

- Start the app by opening any of the files global.R, server.R or ui.R in RStudio (Posit) and press "Run App" on the top right in the source box.

![run app button](docs/run_app.png)

Note that exactly one entry per day and no missing values are assumed. The app might not be working as expected if these assumption are not true.

## Examples

The app contains many different kinds of visualizations. Here are a selected few examples. Note that all data is anonymized for privacy reasons.

![dashboard](docs/dashboard.png)

![force network of related activities](docs/force_network.png)

![mood distribution by quality of sleep](docs/mood_distribution_by_quality_of_sleep.png)

![grocery shopping per weekday](docs/occurences_weekday_shopping.png)

![grocery shopping autocorrelation](docs/shopping_autocorrelation.png)

![correlation between activities with a lag of one day](docs/correlation_lag_1.png)

![average mood depending on how often one went grocery shopping in the last week](docs/average_mood_by_activity_foredays.png)

## Contributing

Anyone interested is invited to contribute via pull requests.