gov-uk-rap-materials_mapping-skills-progress.Rmd

---
title: "Documenting skills development"
author: "Joseph Crispell & Laurie Baker"
date: "`r format(Sys.Date(), '%d %b %Y')`"
output:
  html_document:
    number_sections: yes
    toc: yes
    toc_depth: '2'
    toc_float: yes
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r preparation, include=FALSE}
# Load libraries
library(fmsb)
```

# Introduction

Here is a quick tutorial about mapping our skills progression using R. We're going to be using the [fmsb]() to visualise our skills progress, which we'll install and load with the following code:

```{r install and load, eval=FALSE}
install.packages("fmsb")
library(fmsb)
```

# Our skill areas

We'll look to categorise our skills progress into the following themes:

- **Programming**
- **Statistics**
- **Databases**
- **Projects**
- **Web development**
- **Versioning**

We can then create a `data.frame` that records our current skills point:

```{r define skills table}
# Set you current skills point
skillsPointsCurrent <- data.frame(
  "Programming" = c(5, 1, 4),
  "Statistics" = c(5, 1, 3),
  "Databases" = c(5, 1, 2),
  "Projects" = c(5, 1, 3),
  "Web" = c(5, 1, 3),
  "Versioning" = c(5, 1, 3)
)
rownames(skillsPointsCurrent) <- c("Max level", "Min level", "My level")

skillsPointsCurrent
```

# Visualising our skills point

```{r}
radarchart(skillsPointsCurrent,
  axistype = 1, # Centre axis labels
  title = "Starting Point",
  pcol = rgb(0.2, 0.5, 0.5, 0.6), # Colour of polygon points
  pfcol = rgb(0.2, 0.5, 0.5, 0.5), # COlour of polygon fill
  plwd = 2, # Line width for the polygon
  cglcol = "grey", # COlour of lines in web
  cglty = 1, # Type of line in radar
  axislabcol = "blue", # Skills categories colour
  caxislabels = c("Unaware", "Aware", "Working", "Practitioner", "Expert"), # Skills categories
  cglwd = 0.3, # Width of line for radar
  calcex = 0.75, # Font size for axis labels
  vlcex = 1
) # Font size for skills labels
```


# Thinking about progression

Next, I'd like to consider where I would like to get to with my learning:

```{r where Id like to be}
# Set you goal skills point
skillsPointsGoal <- data.frame(
  "Programming" = c(5, 1, 4),
  "Statistics" = c(5, 1, 4),
  "Databases" = c(5, 1, 3),
  "Projects" = c(5, 1, 4),
  "Web" = c(5, 1, 3),
  "Versioning" = c(5, 1, 5)
)
rownames(skillsPointsGoal) <- c("Max level", "Min level", "My level")

# Plot my goal point
radarchart(skillsPointsGoal,
  axistype = 1, # Centre axis labels
  title = "Where I'd like to be",
  pcol = rgb(0.2, 0.5, 0.5, 0.6), # Colour of polygon
  pfcol = rgb(0.2, 0.5, 0.5, 0.5), # COlour of polygon fill
  plwd = 2, # Line width for the polygon
  cglcol = "grey", # COlour of lines in web
  cglty = 1, # Type of line in radar
  axislabcol = "blue", # Skills categories colour
  caxislabels = c("Unaware", "Aware", "Working", "Practitioner", "Expert"), # Skills categories
  cglwd = 0.3, # Width of line for radar
  calcex = 0.75, # Font size for axis labels
  vlcex = 1
) # Font size for skills labels
```

# Overlaying skills points in a single plot

We can use the [basicPlotteR](https://github.com/JosephCrispell/basicPlotteR/blob/master/README.md#radarchart) R package (shameless self-promotion!) to overlay our skills points in a single plot. Install it with the following code:

```{r install basicPlotteR, eval=FALSE}
install.packages("devtools")
devtools::install_github("JosephCrispell/basicPlotteR")
library(basicPlotteR)
```

```{r load basicPlotteR, echo=FALSE}
library(basicPlotteR)
```

Then create the radar chart with the following code:

```{r radar chart with basicPlotteR}
# Create a chart with my current skills points
radarChart(
  scores = skillsPointsCurrent["My level", ],
  names = colnames(skillsPointsCurrent),
  levels = c("Unaware", "Aware", "Working", "Practitioner", "Expert")
)

# Add my goal onto the same chart
radarChart(
  scores = skillsPointsGoal["My level", ],
  names = colnames(skillsPointsGoal),
  levels = c("Unaware", "Aware", "Working", "Practitioner", "Expert"), add = TRUE,
  polygon.col = "blue"
)

# Add a legend
legend("topright", legend = c("Current", "Goal"), text.col = c("red", "blue"), bty = "n", xpd = TRUE)
```

# Creating an interactive skills map

Lastly, we can use the [plotly](https://plotly.com/r/radar-chart/) R package to create an interactive radar chart. Install plotly with the following code:

```{r install plotly, eval=FALSE}
install.packages("plotly")
library(plotly)
```

```{r load plotly, include=FALSE}
library(plotly)
```

Then create your interactive chart like this:

```{r radar chart with plotly, warning=FALSE}
# Create a radial plot object
fig <- plot_ly(type = "scatterpolar", fill = "toself", mode = "markers")

# Add the first skills point trace - current
fig <- add_trace(fig,
  r = as.numeric(skillsPointsCurrent["My level", ]),
  theta = colnames(skillsPointsCurrent),
  name = "Current"
)

# Add the second skills point trace - my goals
fig <- add_trace(fig,
  r = as.numeric(skillsPointsGoal["My level", ]),
  theta = colnames(skillsPointsGoal),
  name = "Goal"
)

# Add a radial axis
fig <- layout(fig,
  polar = list(
    radialaxis = list(
      visible = TRUE,
      range = c(1, 5),
      tickvals = 1:5,
      ticktext = c("Unaware", "Aware", "Working", "Practitioner", "Expert")
    )
  )
)

# Plot the radial chart
fig
```