---
title: "Data Reshaping Lab"
author: "Data Wrangling in R"
output: html_document
editor_options: 
  chunk_output_type: console
---

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

```{r}
library(tidyverse)
```


0.  Read in the `ChickWeight` dataset. This data is from an experiment on the effect of diet on early growth of chicks. Call it `chicks`.

```{r, message = FALSE}
chicks <- datasets::ChickWeight
```

1. Reshape to wide format using `pivot_wider`. Use the arguments `names_from = Time` and `values_from = weight`. Include the following in the `pivot_wider` function: `names_prefix = "Time_"`to update all the new column names. Call the new data `chicks_wide`.

```{r}

```

2. Filter the data so that `Time_0` is <= 40 and `Time_21` >= 200. Reassign to `chicks_wide`.

```{r}

```

3. Select columns Chick, Diet, `Time_0`, and `Time_21`. Reassign to `chicks_wide`.

```{r}

```

4. Reshape to long format using `pivot_longer`. Pivot the numeric columns. Use the arguments `names_to = ` and `values_to = `. Call the data `chicks_long`.

```{r}

```