--- 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!