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Merge pull request #1 from RamiKrispin/data-refresh-04/22
Data refresh 04/22
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‎.Rbuildignore‎

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^data_raw$
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^LICENSE\.md$
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^CRAN-RELEASE$
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^CRAN-SUBMISSION$

‎CRAN-SUBMISSION‎

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Version: 0.1.2
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Date: 2023-04-16 06:30:52 UTC
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SHA: efb45230dddbd71b96c33b71c990eb6976f18b7f

‎DESCRIPTION‎

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Package: USgas
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Type: Package
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Title: The Demand for Natural Gas in the US
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Version: 0.1.1
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Version: 0.1.2
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Authors@R: person(given = "Rami",
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family ="Krispin",
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email = "rami.krispin@gmail.com",
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LazyData: true
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Depends:
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R (>= 2.10)
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RoxygenNote: 7.1.1
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RoxygenNote: 7.2.1
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URL: https://github.com/RamiKrispin/USgas
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BugReports: https://github.com/RamiKrispin/USgas/issues
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Suggests:
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knitr,
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rmarkdown
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rmarkdown,
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plotly
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VignetteBuilder: knitr

‎NEWS.md‎

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# USgas 0.1.2
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* Add new dataset `usgas`, describing the US monthly natural gas consumption by end-use on the state and US aggregate level
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* Deprecating the previous package datasets - `us_residential`, `us_total`, and `us_total`, as they can be generated by the `usgas` dataset
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# USgas 0.1.1
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* Fixing CRAN errors - removing the `digits` argument from the `format` function

‎R/usgas.R‎

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#' US Monthly Consumption of Natural Gas by End Use
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#' @description The US monthly consumption of natural gas by end-use and state between 1973 (US aggregate, state level since 1989) and 2022.
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#'
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#' Units: Million Cubic Feet
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#'
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#'
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#' @format A data.frame with 6 variables.
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#' \describe{
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#' \item{date}{A Date, the month and year of the observation (the day set by default to 1st of the month)}
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#' \item{process}{The process type description}
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#' \item{state}{The US state name}
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#' \item{state_abb}{the US state abbreviation}
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#' \item{y}{A numeric, the monthly natural gas residential consumption in a million cubic feet}
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#' }
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#' @source US Energy Information Administration (EIA) \href{https://www.eia.gov/}{website}.
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#' @keywords datasets timeseries natural gas us state
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#' @details The dataset contains monthly summary of the consumption of natural gas
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#' by end-use in the US by state and total aggregate level. The data is available
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#' for the state level between January 1989 and December 2022, and for the US level
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#' between January 1973 and Dec 2022. It includes the following end-use categories:
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#'
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#' - Commercial Consumption
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#' - Delivered to Consumers
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#' - Electric Power Consumption
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#' - Industrial Consumption
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#' - Lease and Plant Fuel Consumption
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#' - Pipeline Fuel Consumption
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#' - Residential Consumption
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#' - Vehicle Fuel Consumption
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#'
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#' @examples
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#'
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#' library(plotly)
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#'
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#' data("usgas")
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#'
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#' head(usgas)
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#'
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#' # Plot the US consumption
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#'
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#' us_df <- usgas[which(usgas$state == "U.S."), ]
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#'
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#' plot_ly(data = us_df,
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#' x = ~ date,
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#' y = ~ y,
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#' color = ~ process,
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#' type = "scatter",
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#' mode = "line") |>
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#' layout(title = "US Monthly Consumption by End Use",
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#' yaxis = list(title = "MMCF"),
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#' xaxis = list(title = "Source: EIA Website"),
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#' legend = list(x = 0, y = 1.05),
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#' margin = list(l = 50, r = 50, b = 70, t = 60))
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#'
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#'
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#' # Plot the California consumption
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#'
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#' ca_df <- usgas[which(usgas$state == "California"), ]
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#'
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#' plot_ly(data = ca_df,
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#' x = ~ date,
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#' y = ~ y,
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#' color = ~ process,
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#' type = "scatter",
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#' mode = "line") |>
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#' layout(title = "California Monthly Consumption by End Use",
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#' yaxis = list(title = "MMCF"),
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#' xaxis = list(title = "Source: EIA Website"),
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#' legend = list(x = 0, y = 1.05),
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#' margin = list(l = 50, r = 50, b = 70, t = 60))
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#'
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"usgas"

‎README.Rmd‎

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# USgas <a href='https://ramikrispin.github.io/USgas/'><img src='man/figures/USgas.png' align="right" width="150" height="150" /></a>
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<!-- badges: start -->
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[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/USgas)](https://cran.r-project.org/package=USgas) [![lifecycle](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html) [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT) [![GitHub commit](https://img.shields.io/github/last-commit/RamiKrispin/USgas)](https://github.com/RamiKrispin/USgas/commit/main)
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[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/USgas)](https://cran.r-project.org/package=USgas) [![lifecycle](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html) [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/license/mit/) [![GitHub commit](https://img.shields.io/github/last-commit/RamiKrispin/USgas)](https://github.com/RamiKrispin/USgas/commit/main)
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<!-- badges: end -->
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The **USgas** package provides an overview of demand for natural gas in the US in a time-series format. That includes the following datasets:
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The **USgas** package provides an overview of demand for natural gas in the US in a time-series format. That includes the following dataset:
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* `usgas` - The monthly consumption of natural gas in the US/state level by end-use since 1973 for US level and 1989 for state level. It includes the following end-use categories:
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- Commercial Consumption
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- Delivered to Consumers
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- Electric Power Consumption
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- Industrial Consumption
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- Lease and Plant Fuel Consumption
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- Pipeline Fuel Consumption
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- Residential Consumption
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- Vehicle Fuel Consumption
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The package also includes the following datasets, from previous release:
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* `us_total` - The US annual natural gas consumption by state-level between 1997 and 2019, and aggregate level between 1949 and 2019
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* `us_monthly` - The monthly demand for natural gas in the US between 2001 and 2020
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* `us_residential` - The US monthly natural gas residential consumption by state and aggregate level between 1989 and 2020
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The `us_total`, `us_monthly`, and `us_residential` can be derived out of the `usgas` dataset. Therefore, those datasets in the process of deprication and will be removed in the next release to CRAN.
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Data source: The US Energy Information Administration [API](https://www.eia.gov/)
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More information about the package datasets available on this [vignette](https://ramikrispin.github.io/USgas/articles/introduction.html).
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```
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## Example
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Plotting the consumption of natural gas in New England states:
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Let's load the data:
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```{r}
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data(us_total)
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data("usgas")
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str(us_total)
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head(usgas)
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head(us_total)
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str(usgas)
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```
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Subsetting the New England states:
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Plotting the residential consumption of natural gas in the US:
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``` r
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library(plotly)
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us_res <- usgas[which(usgas$state == "U.S." & usgas$process == "Residential Consumption"), ]
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plot_ly(data = us_res,
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x = ~ date,
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y = ~ y,
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type = "scatter",
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mode = "line") |>
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layout(title = "US Monthly Residential Consumption",
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yaxis = list(title = "MMCF"),
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xaxis = list(title = "Source: EIA API"))
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```
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```{r}
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ne <- c("Connecticut", "Maine", "Massachusetts",
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"New Hampshire", "Rhode Island", "Vermont")
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ne_gas <- us_total[which(us_total$state %in% ne),]
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```{r, include = FALSE}
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library(plotly)
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us_res <- usgas[which(usgas$state == "U.S." & usgas$process == "Residential Consumption"), ]
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p1 <- plot_ly(data = us_res,
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x = ~ date,
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y = ~ y,
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type = "scatter",
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mode = "line") |>
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layout(title = "US Monthly Natural Gas Consumption by Residential Consumers",
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yaxis = list(title = "MMCF"),
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xaxis = list(title = "Source: EIA API"))
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orca(p1, "man/figures/us_res.svg")
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```
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ne_wide <- reshape(ne_gas, v.names = "y", idvar = "year",
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timevar = "state", direction = "wide")
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ne_wide <- ne_wide[order(ne_wide$year), ]
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<img src="man/figures/us_res.svg" width="100%" />
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names(ne_wide) <- c("year",ne)
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head(ne_wide)
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```
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Plotting the states series:
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Plotting the total monthly natural gas delivered in the New England states:
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```{r}
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# Set the y and x axis ticks
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at_x <- seq(from = 2000, to = 2020, by = 5)
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at_y <- pretty(ne_gas$y)[c(2, 4, 6)]
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# plot the first series
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plot(ne_wide$year, ne_wide$Connecticut,
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type = "l",
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col = "#073b4c",
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frame.plot = FALSE,
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axes = FALSE,
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panel.first = abline(h = c(at_y), col = "grey80"),
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main = "New England Annual Natural Gas Consumption by State",
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cex.main = 1.2, font.main = 1, col.main = "black",
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xlab = "Source: https://www.eia.gov/",
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font.axis = 1, cex.lab= 1,
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ylab = "Million Cubic Feet",
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ylim = c(min(ne_gas$y, na.rm = TRUE), max(ne_gas$y, na.rm = TRUE)),
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xlim = c(min(ne_gas$year), max(ne_gas$year) + 3))
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# Add the 5 other series
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lines(ne_wide$year, ne_wide$Maine, col = "#1f77b4")
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lines(ne_wide$year, ne_wide$Massachusetts, col = "#118ab2")
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lines(ne_wide$year, ne_wide$`New Hampshire`, col = "#06d6a0")
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lines(ne_wide$year, ne_wide$`Rhode Island`, col = "#ffd166")
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lines(ne_wide$year, ne_wide$Vermont, col = "#ef476f")
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# Add the y and x axis ticks
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mtext(side =1, text = format(at_x, nsmall=0), at = at_x,
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col = "grey20", line = 1, cex = 0.8)
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mtext(side =2, text = format(at_y, scientific = FALSE), at = at_y,
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col = "grey20", line = 1, cex = 0.8)
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# Add text
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text(max(ne_wide$year) + 2,
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tail(ne_wide$Connecticut,1),
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"Connecticut",
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col = "#073b4c",
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cex = 0.7)
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text(max(ne_wide$year) + 2,
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tail(ne_wide$Maine,1) * 0.95,
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"Maine",
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col = "#1f77b4",
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cex = 0.7)
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text(max(ne_wide$year) + 2,
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tail(ne_wide$Massachusetts,1),
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"Massachusetts",
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col = "#118ab2",
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cex = 0.7)
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text(max(ne_wide$year) + 2,
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tail(ne_wide$`New Hampshire`,1) * 1.1,
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"New Hampshire",
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col = "#06d6a0",
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cex = 0.7)
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text(max(ne_wide$year) + 2,
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tail(ne_wide$`Rhode Island`,1) * 1.05,
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"Rhode Island",
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col = "#ffd166",
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cex = 0.7)
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text(max(ne_wide$year) + 2,
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tail(ne_wide$Vermont,1),
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"Vermont",
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col = "#ef476f",
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cex = 0.7)
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```r
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ne <- c("Connecticut", "Maine", "Massachusetts",
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"New Hampshire", "Rhode Island", "Vermont")
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ne_gas <- usgas[which(usgas$state %in% ne & usgas$process == "Delivered to Consumers"),]
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plot_ly(data = ne_gas,
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x = ~ date,
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y = ~ y,
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color = ~ state,
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type = "scatter",
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mode = "line") |>
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layout(title = "Total Natrual Gas Delivered to Consumers in New England States",
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yaxis = list(title = "MMCF"),
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xaxis = list(title = "Source: EIA API"))
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```
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```{r , include = FALSE}
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ne <- c("Connecticut", "Maine", "Massachusetts",
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"New Hampshire", "Rhode Island", "Vermont")
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ne_gas <- usgas[which(usgas$state %in% ne & usgas$process == "Delivered to Consumers"),]
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p2 <- plot_ly(data = ne_gas,
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x = ~ date,
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y = ~ y,
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color = ~ state,
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type = "scatter",
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mode = "line") |>
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layout(title = "Total Natrual Gas Delivered to Consumers in New England States",
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yaxis = list(title = "MMCF"),
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xaxis = list(title = "Source: EIA API"))
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orca(p2, "man/figures/new_england.svg")
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```
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<img src="man/figures/new_england.svg" width="100%" />

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