Final Project: Midio

Wow! This semester has flown by! Our final project is to create an R package. 

My R package is called Midio. 

It was created to compliment the mood tracking app called Daylio. Daylio Is a highly customizable app that allows the user to track not only mood but activities for each day. Personally, I have been using this app for about 60 days and plan to use it for as long as I can. Daylio allows users to export its data into a CSV file. This data is not user-friendly and difficult to put into any visualizations. My package takes this raw data and transforms it into something user-friendly and ready for analysis using ggplot2. Documentation was created using Roxygen. 

I also included my own 60 days' worth of data to test out. :)

clean <- function(data) 





The first function that I created reformats the full date column into a date instead of a string. This function also makes all activities in lower case.

Another issue is that the activities column has activities in it but is separated by pipes. The second function I made creates a frequency table of activities

activity_cnt <- act_cnt(data)


The third function I made creates a frequency table of activities by mood. 

activity_cnt_m <- act_cnt_m(data)

The fourth function creates a frequency table of activities by day. 

activity_cnt_d <- act_cnt_d(data)

The fifth function creates a frequency table of mood by day.

mood_cnt_d <- mod_cnt_d(data)

The 6th function creates a frequency table of mood by month.

mood_cnt_n <- mod_cnt_n(data)

Then I created two visualization functions using ggplot2. 

Visualize mood by day
day_mood(mood_cnt_d)


















and Visualize activities by top number
top_activity(activity_cnt, 20)


Please see my github to download: https://github.com/Midiquin/Midio

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