# Scotland publishing summaries # Read the preprocessed ESTC data table and load tools: # Load libraries library(ggplot2) library(tidyr) library(dplyr) library(reshape2) library(estc) library(bibliographica) library(dplyr) # Pick Scotland documents only selected_place <- "Edinburgh" sel.country <- "Scotland" dfo <- filter(df.preprocessed, country == sel.country & publication_year >= 1470) dfo$unity <- rep(1, nrow(dfo)) timeinterval <- 5 # Use 5 year intervals
df <- filter(dfo, country == sel.country & publication_year >= 1470) df$publication.timeunit <- round(df$publication_year/timeinterval)*timeinterval publications <- tapply(df$unity, list(df$publication.timeunit, df$publication_place), sum) publications[is.na(publications)] <- 0 # Set NAs to 0 publications <- publications/timeinterval # Instead of decadal sum, use average annual output dfm <- melt(publications) names(dfm) <- c("Time", "Place", "Documents") dfm <- filter(dfm, Place == selected_place) dfm <- transform(dfm, date = as.character(Time)) dfs <- spread(dfm, Place, Documents) dfs$date <- as.numeric(as.character(dfs$date)) dfs$varname <- dfs[[selected_place]] dfs1 <- dfs df <- filter(dfo, country == sel.country & publication_year >= 1470) df <- df[grep("histor", tolower(df$title)),] df$publication.timeunit <- round(df$publication_year/timeinterval)*timeinterval publications <- tapply(df$unity, list(df$publication.timeunit, df$publication_place), sum) publications[is.na(publications)] <- 0 # Set NAs to 0 publications <- publications/timeinterval # Instead of decadal sum, use average annual output dfm <- melt(publications) names(dfm) <- c("Time", "Place", "Documents") dfm <- filter(dfm, Place == selected_place) dfm <- transform(dfm, date = as.character(Time)) dfs <- spread(dfm, Place, Documents) dfs$date <- as.numeric(as.character(dfs$date)) dfs$varname <- dfs[[selected_place]] dfs2 <- dfs # Custom highlight for specific time intervals dfs <- dfs1 rect_left <- c(min(na.omit(dfs$date)), 1642, 1651+1, 1660, 1660+1, 1688, 1689+1, 1706, 1707+1, 1776, 1776+1, max(na.omit(dfs$date))) rectangles <- data.frame( xmin = rect_left[-length(rect_left)], xmax = rect_left[-1], ymin = min(dfs$varname), ymax = max(dfs$varname)) rectangles$shade <- rep(c("White", "Highlight"), length = nrow(rectangles)) # Draw Figure theme_set(theme_bw(20)) p <- ggplot() p <- p + geom_rect(data = rectangles, aes(xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, fill=shade), alpha=0.8) + scale_fill_manual(values = c("gray", "white")) + guides(fill = "none") p <- p + geom_line(data = dfs1, aes(x = date, y = varname), col = "black") p <- p + geom_point(data = dfs1, aes(x = date, y = varname), col = "black") p <- p + geom_line(data = dfs2, aes(x = date, y = varname), col = "darkgray") p <- p + geom_point(data = dfs2, aes(x = date, y = varname), col = "darkgray") p <- p + scale_x_continuous(breaks=seq(min(dfs$date), max(dfs$date), 20)) p <- p + ggtitle(paste("Julkaisutoiminta: ", selected_place)) p <- p + ylab("Dokumenttia / Vuosi") p <- p + scale_y_log10() print(p)
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