---
title: "Data Management for the ____________ Data Set"
author: "PUT YOUR NAME HERE"
format: html
---

# Import
```{r}
# Load libraries
library(tidyverse)

# Read in the data 
raw <- read.delim(here::here("data/Depress.txt")) # change this line to read in YOUR data set

# Select only the variables that I am interested in
mydata  <- raw %>% select()
```



# Clean

## Replace this text with the name of Categorical variable 1
replace this text with a description of what the variable is about

```{r}
# use the class() or str() function to identify the data type
```

Does this match with the intended data type?

```{r}
# create a table() of the data to check for out of range variables
```

write a sentence here explaining if there are any out of range variables


## Replace this text with the name of Categorical variable 2

replace this text with a description of what the variable is about

```{r}
# use the class() or str() function to identify the data type
```

Does this match with the intended data type?

```{r}
# create a table() of the data to check for out of range variables
```

write a sentence here explaining if there are any out of range variables


##  Replace this text with the name of Quantitative variable 1

replace this text with a description of what the variable is about

```{r}
# use the class() or str() function to identify the data type
```

Does this match with the intended data type?

```{r}
# create a summary() of the data to check for out of range variables
# create a hist() histogram of the data to check for severe skewness
```

write a sentence here explaining if there are any out of range variables


##  Replace this text with the name of Quantitative variable 2

replace this text with a description of what the variable is about

```{r}
# use the class() or str() function to identify the data type
```

Does this match with the intended data type?

```{r}
# create a summary() of the data to check for out of range variables
# create a hist() histogram of the data to check for severe skewness
```

write a sentence here explaining if there are any out of range variables




# Export cleaned data set

Keep only selected variables and save to an external file
```{r}
clean <- mydata %>% 
  select()

save(clean, file=here::here("data/depression_clean.Rdata")) # change this line to use the name of YOUR data set (you are not analyzing depression)
```
