7  ACTIVITY: Joins Pivots dataRetrieval

7.1 Load the tidyverse, dataRetrieval, and patchwork packages.

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.2     ✔ readr     2.1.4
✔ forcats   1.0.0     ✔ stringr   1.5.0
✔ ggplot2   3.4.2     ✔ tibble    3.2.1
✔ lubridate 1.9.2     ✔ tidyr     1.3.0
✔ purrr     1.0.1     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

7.2 Problem 1

Using readWQPqw(), read all the chloride (00940) data for the New River at Radford (03171000, must add USGS- to gage id). Use the head() function to print the beginning of the output from this function.

7.3 Problem 2

Using the readNWISdv (daily values) function, download discharge (00060), temperature (00010), and specific conductivity (00095) for the New River at Radford from 2007 to 2009 (regular year). Use renameNWIScolumns() to rename the output of the download. Use head() to show the beginning of the results of your download.

7.4 Problem 3

Join the data from Problem 1 and Problem 2 to add the chloride data to the daily discharge, temp, and conductivity data. hint: you will join on the date. Preview your data below the chunk using head().

7.5 Problem 4

Using the joined data, create a line plot of Date (x) and Flow (y). Create a scatter plot of Date (x) and chloride concentration (y). Put the graphs on top of each other using the patchwork library.

7.6 Problem 5

Create a scatter plot of Specific Conductivity (y) and Chloride (x). Challenge: what could you do to get rid of the warning this plot generates about NAs.

7.7 Problem 6

Read in the GG chem subset data and plot Mg_E1 (x) vs Ca_E1 (y) as points.

7.8 Problem 7

We want to look at concentrations of each element in the #6 dataset along the stream (Distance), which is difficult in the current format. Pivot the data into a long format, the data from Ca, Mg, and Na _E1 columns should be pivoted. Make line plots of each element where y is the concentration and x is distance. Use facet_wrap() to create a separate plot for each element and use the “scales” argument of facet_wrap to allow each plot to have different y limits.