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#install.packages("tidyverse") #install.packages("lubridate") library(tidyverse) library(ggplot2) library(lubridate) #Data input #Read the CSV and then we make a date and datetime columns. #I actually don’t use the datetime column but it’s there if we change our minds. co2data <- read_csv("CO2_13m6_2009til2021.csv") %>% mutate( date = ymd(paste(Year, Month, Day, sep= ' ')), datetime = ymd_hm(paste(Year, Month, Day, Hour, Minute, sep= ' ')), HYY_META.CH4168 <- as.numeric(HYY_META.CO2168) ) colors <- c( "Average" = "black" ) fills <- c( "Quantiles" = "lightgreen", "Min & Max values" = "lightblue" ) theme.eyrun <- theme_classic() + theme( legend.title = element_blank(), legend.spacing.y = unit(-0.1, 'cm'), plot.title = element_text(size=30), axis.title.x = element_text(size=24), plot.margin = unit(c(1,1,1,1), "lines"), axis.title.y = element_text(size=24), axis.text.x = element_text(size=20), axis.text.y= element_text(size=20) ) co2data.plot <- co2data %>% mutate( yearmonth = floor_date(date, "month") ) %>% group_by(yearmonth) %>% summarise( co2.avg = mean(HYY_META.CO2168, na.rm = TRUE), co2.min = min(HYY_META.CO2168, na.rm = TRUE), co2.max = max(HYY_META.CO2168, na.rm = TRUE), co2.q25 = quantile(HYY_META.CO2168, 0.25, na.rm = TRUE), co2.q75 = quantile(HYY_META.CO2168, 0.75, na.rm = TRUE) ) co2data.plot %>% ggplot(aes(x=yearmonth, y=co2.avg)) + geom_ribbon(aes(ymin=co2.min, ymax=co2.max, fill = "Min & Max values"), alpha=0.4) + geom_ribbon(aes(ymin=co2.q25, ymax=co2.q75, fill = "Quantiles"), alpha=0.6) + geom_line(aes(y=co2.avg, color = "Average"), alpha=0.6) + labs( title = "CO2 Concentration, 2012-2021", x = "Year", y = "CO2, ppm" ) + scale_color_manual(name="", values = colors) + scale_fill_manual(name="", values = fills) + scale_y_continuous(breaks = seq(360, 450, by= 10), limits = c(360, 450)) + scale_x_date(date_breaks = '2 year', expand = c(0,0), labels = date_format("%Y")) + theme.eyrun
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