# Install the development version from GitHub: # install.packages("devtools") devtools::install_github("R-CoderDotCom/econocharts")

supply() # Default plot

supply(ncurves = 1, # Number of supply curves to be plotted type = "line", # Type of the curve x = c(2, 4, 5), # Y-axis values where to create intersections linecol = 2, # Color of the curves geom = "label", # Label type of the intersection points geomfill = "pink", # If geom = "label", is the background color of the label main = "Supply curve") # Title of the plot

supply(ncurves = 3, # Three supply curves xlab = "X", # X-axis label ylab = "Y", # Y-axis label bg.col = "lightblue") # Background color

demand(x = 3:6, # Intersections generic = FALSE) # Axis values with the actual numbers

demand(main = "Demand", # Title sub = "curve", # Subtitle xlab = "X", # X-axis label ylab = "Y", # Y-axis label names = "D[1]", # Custom name for the curve geomcol = 2) # Color of the custom name of the curve

sdcurve() # Default supply and demand plot

# Custom data supply1 <- data.frame(x = c(1, 9), y = c(1, 9)) supply1 demand1 <- data.frame(x = c(7, 2), y = c(2, 7)) demand1 supply2 <- data.frame(x = c(2, 10), y = c(1, 9)) supply2 demand2 <- data.frame(x = c(8, 2), y = c(2, 8)) demand2 p <- sdcurve(supply1, # Custom data demand1, supply2, demand2, equilibrium = TRUE, # Calculate the equilibrium bg.col = "#fff3cd") # Background color p + annotate("segment", x = 2.5, xend = 3, y = 6.5, yend = 7, # Add more layers arrow = arrow(length = unit(0.3, "lines")), colour = "grey50")

neolabsup(x = c(2, 3, 5, 7), xlab = "Quantity of\n labor supplied", ylab = "Wage rate")

indifference() # Default indifference curve

indifference(ncurves = 2, # Two curves x = c(2, 4), # Intersections main = "Indifference curves", xlab = "Good X", ylab = "Good Y", linecol = 2, # Color of the curves pointcol = 2) # Color of the intersection points

p <- indifference(ncurves = 2, x = c(2, 4), main = "Indifference curves", xlab = "Good X", ylab = "Good Y") int <- bind_rows(curve_intersect(data.frame(x = 1:1000, y = rep(3, nrow(p$curve))), p$curve + 1)) p$p + geom_segment(data = int, aes(x = 0, y = y, xend = x, yend = y), lty = "dotted") + geom_segment(data = int, aes(x = x, y = 0, xend = x, yend = y), lty = "dotted") + geom_point(data = int, size = 3)

indifference(ncurves = 2, # Two curves type = "pcom", # Perfect complements main = "Indifference curves", sub = "Perfect complements", xlab = "Good X", ylab = "Good Y", bg.col = "#fff3cd", # Background color linecol = 1) # Color of the curve

indifference(ncurves = 5, # Five curves type = "psubs", # Perfect substitutes main = "Indifference curves", sub = "Perfect substitutes", xlab = "Good X", ylab = "Good Y", bg.col = "#fff3cd", # Background color linecol = 1) # Color of the curve

ppf(x = 1:6, # Intersections main = "PPF", geom = "text", generic = TRUE, # Generic axis labels xlab = "X", ylab = "Y", labels = 1:6, acol = 3)$p

p <- ppf(x = 4:6, # Intersections main = "PPF", geom = "text", generic = TRUE, # Generic labels labels = c("A", "B", "C"), # Custom labels xlab = "BIKES", ylab = "CARS", acol = 3) # Color of the area p$p + geom_point(data = data.frame(x = 5, y = 5), size = 3) + geom_point(data = data.frame(x = 2, y = 2), size = 3) + annotate("segment", x = 3.1, xend = 4.25, y = 5, yend = 5, arrow = arrow(length = unit(0.5, "lines")), colour = 3, lwd = 1) + annotate("segment", x = 4.25, xend = 4.25, y = 5, yend = 4, arrow = arrow(length = unit(0.5, "lines")), colour = 3, lwd = 1)

# Data demand <- function(Q) 20 - 0.5 * Q supply <- function(Q) 2 + 0.25 * Q supply_tax <- function(Q) supply(Q) + 5 # Chart tax_graph(demand, supply, supply_tax, NULL)

# Chart with shaded areas tax_graph(demand, supply, supply_tax, shaded = TRUE)

ptvalue(sigma = 0.3, lambda = -2.25, col = 2, # Color of the curve xint = seq(0, 75, 25), # Intersections xintcol = 4, # Color of the intersection segments ticks = TRUE, # Display ticks on the axes xlabels = TRUE, # Display the X-axis tick labels ylabels = TRUE, # Display the Y-axis tick labels by_x = 25, by_y = 50, # Axis steps main = "Prospect Theory Value Function")

laffer(ylab = "T", xlab = "t", acol = "lightblue", # Color of the area pointcol = 4) # Color of the maximum point

laffer(xmax = 20, # Modify the curve t = c(3, 6, 9), # Intersections generic = FALSE, ylab = "T", xlab = "t", acol = "lightblue", # Color of the area alpha = 0.6, # Transparency of the area pointcol = 4) # Color of the maximum point 

# Curves curve1 <- data.frame(Hmisc::bezier(c(1, 8, 9), c(1, 5, 9))) curve2 <- data.frame(Hmisc::bezier(c(1, 3, 9), c(9, 3, 1))) # Calculate the intersections curve_intersection <- curve_intersect(curve1, curve2) # Create the chart ggplot(mapping = aes(x = x, y = y)) + geom_line(data = curve1, color = "red", size = 1) + geom_line(data = curve2, color = "blue", size = 1) + geom_vline(xintercept = curve_intersection$x, linetype = "dotted") + geom_hline(yintercept = curve_intersection$y, linetype = "dotted") + theme_classic()

# Define curves with functions curve1 <- function(q) (q - 10)^2 curve2 <- function(q) q^2 + 2*q + 8 # X-axis range x_range <- 0:5 # Calculate the intersections between the two curves curve_intersection <- curve_intersect(curve1, curve2, empirical = FALSE, domain = c(min(x_range), max(x_range))) # Create your custom plot ggplot(data.frame(x = x_range)) + stat_function(aes(x = x), color = "blue", size = 1, fun = curve1) + stat_function(aes(x = x), color = "red", size = 1, fun = curve2) + geom_vline(xintercept = curve_intersection$x, linetype = "dotted") + geom_hline(yintercept = curve_intersection$y, linetype = "dotted") + theme_classic()

To cite package ‘econocharts’ in publications use: José Carlos Soage González and Andrew Heiss (2020). econocharts: Microeconomics and Macroeconomics Charts Made with 'ggplot2'. R package version 1.0. https://r-coder.com/, https://r-coder.com/economics-charts-r/. A BibTeX entry for LaTeX users is @Manual{, title = {econocharts: Microeconomics and Macroeconomics Charts Made with 'ggplot2'}, author = {José Carlos {Soage González} and Andrew Heiss}, year = {2020}, note = {R package version 1.0}, url = {https://r-coder.com/, https://r-coder.com/economics-charts-r/}, }