| Title: | The Demand for Natural Gas in the US |
|---|---|
| Description: | Provides an overview of the demand for natural gas in the US by state and country level. Data source: US Energy Information Administration <https://www.eia.gov/>. |
| Authors: | Rami Krispin [aut, cre] |
| Maintainer: | Rami Krispin <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.1.2 |
| Built: | 2025-02-04 02:37:46 UTC |
| Source: | https://github.com/ramikrispin/usgas |
The dataset provides information about the total monthly natural gas consumption in the US between 2001 and 2020
Units: Million Cubic Feet
us_monthlyus_monthly
A data.frame with 2 variables.
A Date, the month and year of the observation (the day set by default to 1st of the month)
A numeric, the US monthly total natural gas consumption in a million cubic feet
The dataset contains monthly summary of the total demand for natural gas in the US between 2001 and 2020.
US Energy Information Administration (EIA) website.
data("us_monthly") head(us_monthly) at_x <- seq.Date(from = as.Date("2000-01-01"), to = as.Date("2020-01-01"), by = "5 years") at_y <- pretty(us_monthly$y)[c(2, 4, 6)] plot(us_monthly$date, us_monthly$y, col = "#1f77b4", type = "l", frame.plot = FALSE, axes = FALSE, panel.first = abline(h = at_y, col = "grey80"), main = "US Total Natural Gas Consumption", xlab = "Source: https://www.eia.gov/", ylab = "Million Cubic Feet") mtext(side =1, text = format(at_x, format = "%Y"), at = at_x, col = "grey20", line = 1, cex = 0.8) mtext(side =2, text = format(at_y, scientific = FALSE), at = at_y, col = "grey20", line = 1, cex = 0.8)data("us_monthly") head(us_monthly) at_x <- seq.Date(from = as.Date("2000-01-01"), to = as.Date("2020-01-01"), by = "5 years") at_y <- pretty(us_monthly$y)[c(2, 4, 6)] plot(us_monthly$date, us_monthly$y, col = "#1f77b4", type = "l", frame.plot = FALSE, axes = FALSE, panel.first = abline(h = at_y, col = "grey80"), main = "US Total Natural Gas Consumption", xlab = "Source: https://www.eia.gov/", ylab = "Million Cubic Feet") mtext(side =1, text = format(at_x, format = "%Y"), at = at_x, col = "grey20", line = 1, cex = 0.8) mtext(side =2, text = format(at_y, scientific = FALSE), at = at_y, col = "grey20", line = 1, cex = 0.8)
The US monthly consumption of natural gas by residential consumers by state and aggregate level between 1989 and 2020
Units: Million Cubic Feet
us_residentialus_residential
A data.frame with 3 variables.
A Date, the month and year of the observation (the day set by default to 1st of the month)
A character, the US state indicator
A numeric, the monthly natural gas residential consumption in a million cubic feet
The dataset contains monthly summary of the demand for natural gas by residential consumers in the US by state and total aggregate level. The data is available for the state level between January 1989 and September 2020, and for the US level between January 1973 and September 2020.
US Energy Information Administration (EIA) website.
data("us_residential") # Subsetting the total consumption in the US us_res_total <- us_residential[which(us_residential$state == "U.S."),] us_res_total <- us_res_total[order(us_res_total$date), ] head(us_res_total) at_x <- seq.Date(from = as.Date("1980-01-01"), to = as.Date("2020-01-01"), length.out = 5) at_y <- pretty(us_res_total$y)[c(2, 4, 6)] plot(us_res_total$date, us_res_total$y, col = "#1f77b4", type = "l", frame.plot = FALSE, axes = FALSE, panel.first = abline(h = at_y, col = "grey80"), main = "US Natural Gas Residential Consumption", xlab = "Source: https://www.eia.gov/", ylab = "Million Cubic Feet") mtext(side =1, text = format(at_x, format = "%Y %b"), at = at_x, col = "grey20", line = 1, cex = 0.8) mtext(side =2, text = format(at_y, scientific = FALSE), at = at_y, col = "grey20", line = 1, cex = 0.8) ### Plotting the west cost consumption # Subsetting the west cost states wc_gas <- us_residential[which(us_residential$state %in% c("Alaska", "California", "Oregon", "Washington")),] # Reshape to wide wc_wide <- reshape(wc_gas, v.names = "y", idvar = "date", timevar = "state", direction = "wide") names(wc_wide) <- c("date","Alaska", "California", "Oregon", "Washington") # Reorder the data wc_wide <- wc_wide[order(wc_wide$date), ] # Set the plot y and x axis ticks at_x <- seq.Date(from = as.Date("1990-01-01"), to = as.Date("2020-01-01"), length.out = 4) at_y <- pretty(wc_gas$y)[c(2, 4, 6)] # plot the first series plot(wc_wide$date, wc_wide$Alaska, type = "l", frame.plot = FALSE, axes = FALSE, panel.first = abline(h = c(at_y), col = "grey80"), main = "West Cost Natural Gas Residential Consumption", cex.main = 1, font.main = 1, col.main = "black", xlab = "Source: https://www.eia.gov/", font.axis = 1, cex.lab= 0.7, ylab = "Million Cubic Feet", ylim = c(min(wc_gas$y, na.rm = TRUE), max(wc_gas$y, na.rm = TRUE))) # Add the 3 other series lines(wc_wide$date, wc_wide$California, col = "#1f77b4") lines(wc_wide$date, wc_wide$Oregon, col = "#457b9d") lines(wc_wide$date, wc_wide$Washington, col = "#ef476f") # Add the y and x axis ticks mtext(side =1, text = format(at_x, format = "%Y %b"), at = at_x, col = "grey20", line = 1, cex = 0.8) mtext(side =2, text = format(at_y, scientific = FALSE), at = at_y, col = "grey20", line = 1, cex = 0.8) text(tail(wc_wide$date, 10)[1], max(wc_gas$y, na.rm = TRUE), "California", col = "#1f77b4", cex = 0.6) text(tail(wc_wide$date, 10)[1], max(wc_gas$y, na.rm = TRUE) - 5000, "Washington", col = "#ef476f", cex = 0.6) text(tail(wc_wide$date, 10)[1], max(wc_gas$y, na.rm = TRUE) - 10000, "Oregon", col = "#457b9d", cex = 0.6) text(tail(wc_wide$date, 10)[1], max(wc_gas$y, na.rm = TRUE) - 15000, "Alaska", col = "black", cex = 0.6)data("us_residential") # Subsetting the total consumption in the US us_res_total <- us_residential[which(us_residential$state == "U.S."),] us_res_total <- us_res_total[order(us_res_total$date), ] head(us_res_total) at_x <- seq.Date(from = as.Date("1980-01-01"), to = as.Date("2020-01-01"), length.out = 5) at_y <- pretty(us_res_total$y)[c(2, 4, 6)] plot(us_res_total$date, us_res_total$y, col = "#1f77b4", type = "l", frame.plot = FALSE, axes = FALSE, panel.first = abline(h = at_y, col = "grey80"), main = "US Natural Gas Residential Consumption", xlab = "Source: https://www.eia.gov/", ylab = "Million Cubic Feet") mtext(side =1, text = format(at_x, format = "%Y %b"), at = at_x, col = "grey20", line = 1, cex = 0.8) mtext(side =2, text = format(at_y, scientific = FALSE), at = at_y, col = "grey20", line = 1, cex = 0.8) ### Plotting the west cost consumption # Subsetting the west cost states wc_gas <- us_residential[which(us_residential$state %in% c("Alaska", "California", "Oregon", "Washington")),] # Reshape to wide wc_wide <- reshape(wc_gas, v.names = "y", idvar = "date", timevar = "state", direction = "wide") names(wc_wide) <- c("date","Alaska", "California", "Oregon", "Washington") # Reorder the data wc_wide <- wc_wide[order(wc_wide$date), ] # Set the plot y and x axis ticks at_x <- seq.Date(from = as.Date("1990-01-01"), to = as.Date("2020-01-01"), length.out = 4) at_y <- pretty(wc_gas$y)[c(2, 4, 6)] # plot the first series plot(wc_wide$date, wc_wide$Alaska, type = "l", frame.plot = FALSE, axes = FALSE, panel.first = abline(h = c(at_y), col = "grey80"), main = "West Cost Natural Gas Residential Consumption", cex.main = 1, font.main = 1, col.main = "black", xlab = "Source: https://www.eia.gov/", font.axis = 1, cex.lab= 0.7, ylab = "Million Cubic Feet", ylim = c(min(wc_gas$y, na.rm = TRUE), max(wc_gas$y, na.rm = TRUE))) # Add the 3 other series lines(wc_wide$date, wc_wide$California, col = "#1f77b4") lines(wc_wide$date, wc_wide$Oregon, col = "#457b9d") lines(wc_wide$date, wc_wide$Washington, col = "#ef476f") # Add the y and x axis ticks mtext(side =1, text = format(at_x, format = "%Y %b"), at = at_x, col = "grey20", line = 1, cex = 0.8) mtext(side =2, text = format(at_y, scientific = FALSE), at = at_y, col = "grey20", line = 1, cex = 0.8) text(tail(wc_wide$date, 10)[1], max(wc_gas$y, na.rm = TRUE), "California", col = "#1f77b4", cex = 0.6) text(tail(wc_wide$date, 10)[1], max(wc_gas$y, na.rm = TRUE) - 5000, "Washington", col = "#ef476f", cex = 0.6) text(tail(wc_wide$date, 10)[1], max(wc_gas$y, na.rm = TRUE) - 10000, "Oregon", col = "#457b9d", cex = 0.6) text(tail(wc_wide$date, 10)[1], max(wc_gas$y, na.rm = TRUE) - 15000, "Alaska", col = "black", cex = 0.6)
The dataset provides information on the US annual natural gas consumption by state level between 1997 and 2019, and aggregate level between 1949 and 2019
Units: Million Cubic Feet
us_totalus_total
A data.frame with 3 variables.
An integer, the year of the observation
A character, the US state indicator
A numeric, the yearly total natural gas consumption in a million cubic feet by state or US aggregate
The dataset contains a summary of the total annual demand for natural gas in the US by state and total aggregate level. The data is available for the state level between 1997 and 2019, and for the US level between 1949 and 2019.
US Energy Information Administration (EIA) website.
data("us_total") # Subsetting the total consumption in the US us_agg <- us_total[which(us_total$state == "U.S."),] us_agg <- us_agg[order(us_agg$year), ] head(us_agg) at_x <- seq(from = 1950, to = 2020, by = 10) at_y <- pretty(us_agg$y)[c(3, 5, 7)] plot(us_agg$year, us_agg$y, col = "#1f77b4", type = "l", frame.plot = FALSE, axes = FALSE, panel.first = abline(h = at_y, col = "grey80"), main = "US Total Natural Gas Consumption", xlab = "Source: https://www.eia.gov/", ylab = "Million Cubic Feet") mtext(side =1, text = format(at_x, nsmall=0), at = at_x, col = "grey20", line = 1, cex = 0.8) mtext(side =2, text = format(at_y, scientific = FALSE), at = at_y, col = "grey20", line = 1, cex = 0.8) ### Plotting the annual consumption in New England states # Subsetting the New England states ne <- c("Connecticut", "Maine", "Massachusetts", "New Hampshire", "Rhode Island", "Vermont") ne_gas <- us_total[which(us_total$state %in% ne),] # Reshape to wide ne_wide <- reshape(ne_gas, v.names = "y", idvar = "year", timevar = "state", direction = "wide") names(ne_wide) <- c("year",ne) # Reorder the data ne_wide <- ne_wide[order(ne_wide$year), ] # Set the plot y and x axis ticks at_x <- seq(from = 2000, to = 2020, by = 5) at_y <- pretty(ne_gas$y)[c(2, 4, 6)] # plot the first series plot(ne_wide$year, ne_wide$Connecticut, type = "l", col = "#073b4c", frame.plot = FALSE, axes = FALSE, panel.first = abline(h = c(at_y), col = "grey80"), main = "New England Annual Natural Gas Consumption by State", cex.main = 1, font.main = 1, col.main = "black", xlab = "Source: https://www.eia.gov/", font.axis = 1, cex.lab= 0.7, ylab = "Million Cubic Feet", ylim = c(min(ne_gas$y, na.rm = TRUE), max(ne_gas$y, na.rm = TRUE)), xlim = c(min(ne_gas$year), max(ne_gas$year) + 3)) # Add the 5 other series lines(ne_wide$year, ne_wide$Maine, col = "#1f77b4") lines(ne_wide$year, ne_wide$Massachusetts, col = "#118ab2") lines(ne_wide$year, ne_wide$`New Hampshire`, col = "#06d6a0") lines(ne_wide$year, ne_wide$`Rhode Island`, col = "#ffd166") lines(ne_wide$year, ne_wide$Vermont, col = "#ef476f") # Add the y and x axis ticks mtext(side =1, text = format(at_x, nsmall=0), at = at_x, col = "grey20", line = 1, cex = 0.8) mtext(side =2, text = format(at_y, scientific = FALSE), at = at_y, col = "grey20", line = 1, cex = 0.8) text(max(ne_wide$year) + 2, tail(ne_wide$Connecticut,1), "Connecticut", col = "#073b4c", cex = 0.7) text(max(ne_wide$year) + 2, tail(ne_wide$Maine,1) * 0.95, "Maine", col = "#1f77b4", cex = 0.7) text(max(ne_wide$year) + 2, tail(ne_wide$Massachusetts,1), "Massachusetts", col = "#118ab2", cex = 0.7) text(max(ne_wide$year) + 2, tail(ne_wide$`New Hampshire`,1) * 1.1, "New Hampshire", col = "#06d6a0", cex = 0.7) text(max(ne_wide$year) + 2, tail(ne_wide$`Rhode Island`,1) * 1.05, "Rhode Island", col = "#ffd166", cex = 0.7) text(max(ne_wide$year) + 2, tail(ne_wide$Vermont,1), "Vermont", col = "#ef476f", cex = 0.7)data("us_total") # Subsetting the total consumption in the US us_agg <- us_total[which(us_total$state == "U.S."),] us_agg <- us_agg[order(us_agg$year), ] head(us_agg) at_x <- seq(from = 1950, to = 2020, by = 10) at_y <- pretty(us_agg$y)[c(3, 5, 7)] plot(us_agg$year, us_agg$y, col = "#1f77b4", type = "l", frame.plot = FALSE, axes = FALSE, panel.first = abline(h = at_y, col = "grey80"), main = "US Total Natural Gas Consumption", xlab = "Source: https://www.eia.gov/", ylab = "Million Cubic Feet") mtext(side =1, text = format(at_x, nsmall=0), at = at_x, col = "grey20", line = 1, cex = 0.8) mtext(side =2, text = format(at_y, scientific = FALSE), at = at_y, col = "grey20", line = 1, cex = 0.8) ### Plotting the annual consumption in New England states # Subsetting the New England states ne <- c("Connecticut", "Maine", "Massachusetts", "New Hampshire", "Rhode Island", "Vermont") ne_gas <- us_total[which(us_total$state %in% ne),] # Reshape to wide ne_wide <- reshape(ne_gas, v.names = "y", idvar = "year", timevar = "state", direction = "wide") names(ne_wide) <- c("year",ne) # Reorder the data ne_wide <- ne_wide[order(ne_wide$year), ] # Set the plot y and x axis ticks at_x <- seq(from = 2000, to = 2020, by = 5) at_y <- pretty(ne_gas$y)[c(2, 4, 6)] # plot the first series plot(ne_wide$year, ne_wide$Connecticut, type = "l", col = "#073b4c", frame.plot = FALSE, axes = FALSE, panel.first = abline(h = c(at_y), col = "grey80"), main = "New England Annual Natural Gas Consumption by State", cex.main = 1, font.main = 1, col.main = "black", xlab = "Source: https://www.eia.gov/", font.axis = 1, cex.lab= 0.7, ylab = "Million Cubic Feet", ylim = c(min(ne_gas$y, na.rm = TRUE), max(ne_gas$y, na.rm = TRUE)), xlim = c(min(ne_gas$year), max(ne_gas$year) + 3)) # Add the 5 other series lines(ne_wide$year, ne_wide$Maine, col = "#1f77b4") lines(ne_wide$year, ne_wide$Massachusetts, col = "#118ab2") lines(ne_wide$year, ne_wide$`New Hampshire`, col = "#06d6a0") lines(ne_wide$year, ne_wide$`Rhode Island`, col = "#ffd166") lines(ne_wide$year, ne_wide$Vermont, col = "#ef476f") # Add the y and x axis ticks mtext(side =1, text = format(at_x, nsmall=0), at = at_x, col = "grey20", line = 1, cex = 0.8) mtext(side =2, text = format(at_y, scientific = FALSE), at = at_y, col = "grey20", line = 1, cex = 0.8) text(max(ne_wide$year) + 2, tail(ne_wide$Connecticut,1), "Connecticut", col = "#073b4c", cex = 0.7) text(max(ne_wide$year) + 2, tail(ne_wide$Maine,1) * 0.95, "Maine", col = "#1f77b4", cex = 0.7) text(max(ne_wide$year) + 2, tail(ne_wide$Massachusetts,1), "Massachusetts", col = "#118ab2", cex = 0.7) text(max(ne_wide$year) + 2, tail(ne_wide$`New Hampshire`,1) * 1.1, "New Hampshire", col = "#06d6a0", cex = 0.7) text(max(ne_wide$year) + 2, tail(ne_wide$`Rhode Island`,1) * 1.05, "Rhode Island", col = "#ffd166", cex = 0.7) text(max(ne_wide$year) + 2, tail(ne_wide$Vermont,1), "Vermont", col = "#ef476f", cex = 0.7)
The US monthly consumption of natural gas by end-use and state between 1973 (US aggregate, state level since 1989) and 2022.
Units: Million Cubic Feet
usgasusgas
A data.frame with 6 variables.
A Date, the month and year of the observation (the day set by default to 1st of the month)
The process type description
The US state name
the US state abbreviation
A numeric, the monthly natural gas residential consumption in a million cubic feet
The dataset contains monthly summary of the consumption of natural gas by end-use in the US by state and total aggregate level. The data is available for the state level between January 1989 and December 2022, and for the US level between January 1973 and Dec 2022. It includes the following end-use categories:
- Commercial Consumption - Delivered to Consumers - Electric Power Consumption - Industrial Consumption - Lease and Plant Fuel Consumption - Pipeline Fuel Consumption - Residential Consumption - Vehicle Fuel Consumption
US Energy Information Administration (EIA) website.
library(plotly) data("usgas") head(usgas) # Plot the US consumption us_df <- usgas[which(usgas$state == "U.S."), ] plot_ly(data = us_df, x = ~ date, y = ~ y, color = ~ process, type = "scatter", mode = "line") |> layout(title = "US Monthly Consumption by End Use", yaxis = list(title = "MMCF"), xaxis = list(title = "Source: EIA Website"), legend = list(x = 0, y = 1.05), margin = list(l = 50, r = 50, b = 70, t = 60)) # Plot the California consumption ca_df <- usgas[which(usgas$state == "California"), ] plot_ly(data = ca_df, x = ~ date, y = ~ y, color = ~ process, type = "scatter", mode = "line") |> layout(title = "California Monthly Consumption by End Use", yaxis = list(title = "MMCF"), xaxis = list(title = "Source: EIA Website"), legend = list(x = 0, y = 1.05), margin = list(l = 50, r = 50, b = 70, t = 60))library(plotly) data("usgas") head(usgas) # Plot the US consumption us_df <- usgas[which(usgas$state == "U.S."), ] plot_ly(data = us_df, x = ~ date, y = ~ y, color = ~ process, type = "scatter", mode = "line") |> layout(title = "US Monthly Consumption by End Use", yaxis = list(title = "MMCF"), xaxis = list(title = "Source: EIA Website"), legend = list(x = 0, y = 1.05), margin = list(l = 50, r = 50, b = 70, t = 60)) # Plot the California consumption ca_df <- usgas[which(usgas$state == "California"), ] plot_ly(data = ca_df, x = ~ date, y = ~ y, color = ~ process, type = "scatter", mode = "line") |> layout(title = "California Monthly Consumption by End Use", yaxis = list(title = "MMCF"), xaxis = list(title = "Source: EIA Website"), legend = list(x = 0, y = 1.05), margin = list(l = 50, r = 50, b = 70, t = 60))