Project2_Dataset2

Author

Nick Weiner

Introduction

For Project 2, our objective is to make 3 different ELT pipelines for 3 different wide-format .csv files.

For this set of data, I am looking at Landfill emissions. Particularly, I would like to dive deeper into Emission reduction statistics per state.

The Code

library(knitr)

Warning: package 'knitr' was built under R version 4.5.3

library(tidyverse)

Warning: package 'tidyverse' was built under R version 4.5.3

Warning: package 'ggplot2' was built under R version 4.5.3

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.2.0     ✔ readr     2.2.0
✔ forcats   1.0.1     ✔ stringr   1.6.0
✔ ggplot2   4.0.3     ✔ tibble    3.3.1
✔ lubridate 1.9.5     ✔ tidyr     1.3.2
✔ purrr     1.2.1     
── 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

library(lubridate)

I will load in my .csv of Emissions data from December 2019.

Landfill <- read.csv("2019Dec_lmopdata.xlsx - LMOP Database.csv")

I first want to remove a lot of columns that don’t add value to my analysis, then I would like to rename and pivot the data to be longer

Landfill1 <- Landfill |>
  drop_na(Actual.MW.Generation:Current.Year.Emission.Reductions..MMTCO2e.yr....Avoided) |>
  select(-c(1,2,5,7,8,9,10,12,13,14,15,16,17,18,21,22,23,24,25,26,27,28))|>
  rename(
    "Emissions_Reduction_Avoided_MMTCO2E" = "Current.Year.Emission.Reductions..MMTCO2e.yr....Avoided",
    "Emissions_Reduction_Direct_MMTCO2E" = "Current.Year.Emission.Reductions..MMTCO2e.yr....Direct",
  ) |>
  pivot_longer(LFG.Collected..mmscfd.:Emissions_Reduction_Avoided_MMTCO2E)

Now that I have the data in this format, I would like to group by state, and calculate the sum of emissions direct & avoided data, and graph it all out for a visual comparison of the different states. Unforutnately this is as far as I could get before I reach midnight on 10/11, so I will stop here. If I can submit and commit past the submission time, I will finish the assignment.

Landfill2 <- Landfill1 |> group_by(State) |> filter(name == c(Emissions_Reduction_Direct_MMTCO2E, Emissions_Reduction_Avoided_MMTCO2E)) summarize(Emissions_Reduction_Avoided = sum(name, na.rm = TRUE), Emissions_Reduction_Direct = sum(Emissions_Reduction_Direct_MMTCO2E, na.rm = TRUE))