Challenge 9

Creating a function

Author

Shuqi Hong

Published

June 29, 2023

library(tidyverse)
library(ggplot2)

knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)

Challenge Overview

Today’s challenge is simple. Create a function, and use it to perform a data analysis / cleaning / visualization task:

Examples of such functions are: 1) A function that reads in and cleans a dataset.
2) A function that computes summary statistics (e.g., computes the z score for a variable).
3) A function that plots a histogram.

That’s it!

#A function that computes summary statistics

My.Mean <- function(x) { 
  
  Output <- sum(x) / length(x)
  
  return(Output)
  
}
My.Mean(0:10)

[1] 5

#A function that plots a histogram

My.Hist <- function(x, add.median = T, add.mean = T, add.legend = T) {
  
  hist(x)
  
  if(add.median == T) {abline(v = median(x), lwd = 3)}
  
  if(add.mean == T) {abline(v = mean(x), lty = 2, lwd = 3)}
  
  if(add.legend == T) {
    
    legend("topright", c("median", "mean"), lwd = c(3, 3), lty = c(1, 2))
    
  }
}

My.Hist(rexp(100), add.median = T, add.mean = T, add.legend = T)

---
title: "Challenge 9"
author: "Shuqi Hong"
description: "Creating a function"
date: "6/29/2023"
format:
  html:
    toc: true
    code-copy: true
    code-tools: true
    df-print: paged
---

```{r}
#| label: setup
#| warning: false
#| message: false

library(tidyverse)
library(ggplot2)

knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)
```

## Challenge Overview

Today's challenge is simple. Create a function, and use it to perform a data analysis / cleaning / visualization task:

Examples of such functions are:
1) A function that reads in and cleans a dataset.  
2) A function that computes summary statistics (e.g., computes the z score for a variable).  
3) A function that plots a histogram.  

That's it!


#A function that computes summary statistics

```{r}
My.Mean <- function(x) { 
  
  Output <- sum(x) / length(x)
  
  return(Output)
  
}
My.Mean(0:10)

```

#A function that plots a histogram
```{r}
My.Hist <- function(x, add.median = T, add.mean = T, add.legend = T) {
  
  hist(x)
  
  if(add.median == T) {abline(v = median(x), lwd = 3)}
  
  if(add.mean == T) {abline(v = mean(x), lty = 2, lwd = 3)}
  
  if(add.legend == T) {
    
    legend("topright", c("median", "mean"), lwd = c(3, 3), lty = c(1, 2))
    
  }
}

My.Hist(rexp(100), add.median = T, add.mean = T, add.legend = T)

```