readme.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->


```{r setup, include=FALSE,echo=FALSE}
knitr::opts_chunk$set(
  echo = F, message = F, warning = F,
  fig.path = "man/figures/",
  collapse = T,
  comment = "#>"
  )

library(jsmp)
```


# jsmp

<br>

This package does variety of things I find useful when working with R Tidyverse:

- [Import commonly used packages](#imported-packages)
- [Changes the default ggplot theme](#custom-ggplot-theme)
- [Overrides dplyr::summarise to remove leftover grouping](#general-functions)
- [Contains various functions for use with ggplot](#ggplot-functions)
- [Contains various functions for use in tidy code](#general-functions)

<br>

## Installation

`devtools::install_github("ymer/jsmp")`

<br>

## Custom ggplot theme

```{r, fig.width = 4, fig.height = 3}
mtcars |> ggplot(aes(x = mpg, y = disp)) +
   geom_point()
```

<br>

## ggplot functions


- `gg_hist_percent` : Draws a histogram with y-axis as a percentage

- `gg_legend_remove` : Removes the legend

- `gg_legend_notitle` : Removes the legend title

- `gg_legend_bottom` : Moves the legend to the bottom of the plot

- `gg_loess_line` : Plots a locally weighed regression line

- `gg_regression_line` : Plots a regression line

- `gg_x_remove` : Removes the x-axis

- `gg_x_rotate` : Rotates x-axis labels 45&deg;

- `gg_x_wrap` : Wraps text on x-axis labels

- `gg_y_big` : Changes the y-axis to avoid scientific notation for big numbers

- `gg_y_percent` : Changes the y-axis to percentage

- `gg_y_percent_zero` : Changes the y-axis to percentage, and adjusts the y-axis to start at 0.

- `gg_y_remove` : Removes the y-axis

- `gg_y_zero` : Adjusts the y-axis to start at exactly 0


<br>

## General functions

- `summarise` : Overrides the standard summarise function, so that leftover grouping is dropped after summarising

```{r, echo = T}
mtcars |> 
   group_by(am, gear) |> 
   dplyr::summarise(mean_mpg = mean(mpg)) |> 
   group_vars()
```

```{r, echo = T}
mtcars |> 
   group_by(am, gear) |> 
   summarise(mean_mpg = mean(mpg)) |> 
   group_vars()
```
<br>

- `%notin%` : As `%in%` but exclusionary

<br>

- `d` : Formats table (using `gt` as base)

<br>

- `ci_means` : Finds the means and confidence intervals

```{r, echo = T, fig.width = 4, fig.height = 3}
ToothGrowth |> 
   group_by(supp) |> 
   ci_means(len) |> 
   ggplot(aes(y = supp, x = mean)) +
   geom_crossbar(aes(xmin = ci.lower, xmax = ci.upper), width = 0.3, size = 0.7, color = c1)
```

<br>

- `ci_proportions` : Finds the proportions and confidence intervals

```{r, echo = T, fig.width = 4, fig.height = 3}
mtcars |> 
   mutate(cyl = as.character(cyl)) |> 
   count(cyl) |> 
   mutate(total = sum(n)) |> 
   ci_proportions() |> 
   ggplot(aes(x = cyl, y = proportion)) +
   geom_col(position = position_dodge()) +
   gg_y_percent_zero() +
   gg_legend_notitle() +
   labs(y = "", x = "") +
   geom_errorbar(aes(ymin = ci.lower, ymax = ci.upper),
                  width=.2, position=position_dodge(.9))
```

<br>

- `do_if` : Use a condition in a pipe flow

```{r, echo = T}
only_high_values <- T
mtcars |> do_if(only_high_values, ~ . |> filter(disp > 180)) |> 
   summarise(mean(disp))
```

```{r, echo = T}
only_high_values <- F
mtcars |> do_if(only_high_values, ~ . |> filter(disp > 180)) |> 
   summarise(mean(disp))
```

```{r, echo = T}
high_or_low <- "low"
mtcars |> do_if(high_or_low == "high", 
                 ~ .x |> filter(disp >= 180), 
                 ~ .x |> filter(disp < 180)) |> 
   summarise(mean(disp))
```

<br>

- `filter_duplicates` : selects duplicated rows

```{r, echo = T}
mtcars |> filter_duplicates(wt)
```

<br>

- `fix_names` : Changes the column names to tidy style

```{r, echo = T}
iris |> fix_names() |> 
   head()
```

<br>

- `left_join0` : Performs a left_join, while setting values in missing rows to 0 instead of NA.

```{r, echo = T}
df1 <- tribble(
   ~id, ~v1,
   1, 2,
   2, 2,
   3, 10)

df2 <- tribble(
   ~id, ~v2,
   1, 2,
   3, 4)

left_join(df1, df2)
```

```{r, echo = T}
left_join0(df1, df2)
```

<br>

- `percent` : Returns proportion formatted as percentage

```{r, echo = T}
percent(0.173234235)
```

<br>

- `rows` :  Facilitates looping

```{r, echo = T}
df <- mtcars |> head()
for (row in rows(df)){
   print(row$mpg)
}
```

<br>

- `tab` : Ordered `count` including percentage

```{r, echo = T}
ToothGrowth |>
   filter(len > 20) |> 
   tab(supp)
```

<br>

- `transpose` : Flips rows and columns

```{r, echo = T}
mtcars |> 
   rownames_to_column() |> 
   transpose()
```

<br>

## Imported packages

- [broom](https://github.com/tidymodels/broom)
- [glue](https://github.com/tidyverse/glue)
- [gt](https://github.com/rstudio/gt)
- [lubridate](https://github.com/tidyverse/lubridate)
- [magrittr](https://github.com/tidyverse/magrittr)
- [patchwork](https://github.com/thomasp85/patchwork)
- [stringr](https://stringr.tidyverse.org/)
- [tidyverse](https://github.com/tidyverse/tidyverse)