nerdOut.Rmd

---
title: "FitNotes"
author: "Roberto Siani"
date: "9/10/2020"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(ggplot2)
library(tidyverse)
library(viridis)
library(plotly)
library(lubridate)
library(skimr) # for descriptive statistics
library(ggpubr)

setwd("~/LIBRARY/XLSX/FitNotes/")
```

### IMPORT CSV

```{r}
DF = read.csv("FitNotes_Export_2020_09_18_08_47_10.csv") %>% # import
  filter(Reps != 0 & # filter 1RM failed attempt
           Exercise %in% c("Decline Barbell Bench Press",
                         "Sumo Deadlift",
                         "Barbell Squat",
                         "Overhead Press")) %>% # select your strength metrics 
  select(!c(Distance, Distance.Unit, Time)) %>% 
  mutate(Volume = `Weight..kgs.` * Reps, # calculate volume
         Date = as.Date(Date, 
                        format = "%Y-%m-%d"), # reformat dates
         OneRM = `Weight..kgs.` / ( 1.0278 - 0.0278 * Reps ), # calculate 1RepMax with Brzycki's Formula (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3525823/)
         Perc1RM = `Weight..kgs.` / OneRM * 100) %>% #  calculate percentage of 1RepMax used
  arrange(Exercise)  # arrange by any variable, I prefer having the exercises grouped together 


skimmed = skim(DF)
```

### VISUAL

```{r}
visual = ggplot(DF, aes(x = Date, 
                        y = OneRM,
                        color = Exercise)) +
  geom_smooth(method = "lm", 
              aes(fill = Exercise)) +
  geom_point(aes(y = OneRM,
                 alpha = Perc1RM)) +
  theme_minimal() + 
  theme(panel.grid.minor = element_blank(),
        axis.text.x = element_text(angle = 45,
                                   vjust = 1.25,
                                   hjust = 1),
        axis.title.x = element_blank(),
        text = element_text(size = 15),
        legend.position = "none") +
  scale_x_date(Date, 
               date_breaks = "5 day", 
               breaks = waiver()) +
  facet_wrap(DF$Exercise) +
  scale_color_viridis(discrete = T) +
  scale_fill_viridis(discrete = T)

visual

ggplotly(visual)

```

```{r}

lDF = DF %>% 
  select(!c(Volume, Reps)) %>% 
  pivot_longer(cols = 4:6,
               names_to = "Metric",
               values_to = "Value")


visual2 = ggplot(lDF,
                 aes(x = Metric,
                     y = Value,
                     fill = Exercise,
                     alpha = 0.75)) +
  geom_boxplot() +
  theme_minimal() +
  facet_wrap("Exercise")  + 
  theme(panel.grid.minor = element_blank(),
        axis.text.x = element_text(angle = 45,
                                   vjust = 1.25,
                                   hjust = 1),
        axis.title.x = element_blank(),
        text = element_text(size = 15)) +
  scale_fill_viridis(discrete = T) +
  theme(legend.position = "none")
  


visual2

ggplotly(visual2)

```