---
title: "Exploration of Cereal Data"
output:
  html_document: default
  pdf_document: default
---
## Setup


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

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


## The Data

```{r read_data}
cereals <- read_csv("https://www.dropbox.com/s/ll2c9drmlom1ony/cereals.csv?dl=1")
```

Documentation for dataset: https://www.kaggle.com/crawford/80-cereals/version/2

```{r check_data, eval = FALSE}
#### Edit this code to examine your dataset
```


[Briefly summarize the dataset here.]

[CHECKPOINT:  Knit your Markdown file!]

## Data Cleaning and Transformation

```{r}
#### clean the data

```


```{r summarize}
#### Write code to show the mean and median and sd of sugar content per serving of all cereals


```

```{r summarize2}
#### Write code to show the total calories of all cereals

```


```{r mutate}
#### Write code to create the variable "cal_per_cup" here

```

```{r filter_select}
#### Write code to include only Kellogg brand cereals, and only relevant columns

```


```{r arrange}
#### Write code to sort the dataset by calories per cup


```

```{r wrangle}

#### Combine all steps into one pipeline
  
```



[CHECKPOINT: Knit your document!]

## Visualizing the data

```{r}
#### Make a plot
```



## Conclusion

What did you learn about cereals?  Write a few sentences summarizing your findings, knit your document, and admire your handiwork!
