Task1.Rmd

---
title: "Task 1. Exploring Stream Flow"
author: "John Fay"
date: " Fall 2019"
output: html_document
editor_options: 
  chunk_output_type: console
---

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

# Overview
 1. Prepping your workspace for analysis
 2. Getting the data into the R workspace
 3. Tidying the data
 4. Exploratory data analysis
 5. Comparing streamflow before and after Falls Lake dam constuction
 
# 1. Prepping your workspace for analysis

```{r Installing and loading libraries}
#Install the tidyverse package onto your machine
install.packages('tidyverse')

#Load the tidyverse package into this session
library(tidyverse)

```

# 2. Getting the data into R with `rvest`
 * See https://readr.tidyverse.org/reference/read_delim.html for more information
```{r Get the data}
#Get the URL 
url = 'http://waterservices.usgs.gov/nwis/dv/?format=rdb&sites=02087500&startDT=1930-10-01&endDT=2017-09-30&statCd=00003&parameterCd=00060&siteStatus=all'
#Read the data (tab separated) into a dataframe, skipping metadata lines, and assigning column names
theData <- read_tsv(file = url,
                   skip=30,
                   col_names = c('agency_cd','site_no','datetime','MeanFlow_cfs','Confidence'),
                   )

#Display the data (first 5 rows)
head(theData)

#Display the column names
colnames(theData)

#Display the structure of the dataframe
str(theData)

#Display the dimensions of the dataframe
dim(theData)

#Display the first 10 records of a single column of data
theData$MeanFlow_cfs[1:10]

#Display a summary of the data
summary(theData)

#Display summary of one data column
summary(theData$MeanFlow_cfs)

```

# 3. Tidy the data: 
 * Set the datetime column as a date-time column type
```{r set date}
theData$datetime2 <- as.Date(theData$datetime,format = "%y-%m-%d")
str(theData)

```

 * Add a column for water flow in CMS
```{r calccms}
#Create cms column to plot cubic meters per second
theData$Flow_cms <- neuse$Flow*0.028316847
  summary(neuse$Flow_cms)
```