rggplot2plothistogramoverlay
Is there a way to make a histogram in R to display both the frequency of years an event occurred and a specific detail about that event?
I am trying to create a histogram that will display events that occurred during specific years as either fatal or non-fatal. I am able to create a histogram or yearly occurrences of these events fine in base R by using:
Confirmed_Unprovoked_Attacks_ALL <- read.csv("/path to csv/.csv")
hist(Confirmed_Unprovoked_Attacks_ALL$year, main = 'Confirmed Unprovoked Attacks', ylab = 'Number of Attacks', xlab = 'Year', breaks = 100, xlim = c(1850,2050))
However if it is possible I would like to overlay onto the same (or similar) histogram that is produced by this by coloring these events to distinguish if they were either fatal or non-fatal for that year. I have assigned numeric values to either of these conditions with "1" representing fatal and "2" representing non-fatal.
Here is what the data in the .csv file looks like:
dput((Confirmed_Unprovoked_Attack_ALL))
structure(list(year = c(1876L, 1890L, 1890L, 1894L, 1907L, 1907L,
1909L, 1916L, 1916L, 1916L, 1922L, 1922L, 1926L, 1930L, 1934L,
1935L, 1935L, 1936L, 1936L, 1936L, 1937L, 1937L, 1950L, 1950L,
1951L, 1951L, 1952L, 1953L, 1954L, 1955L, 1955L, 1956L, 1956L,
1956L, 1956L, 1957L, 1957L, 1959L, 1959L, 1960L, 1960L, 1960L,
1960L, 1960L, 1961L, 1961L, 1962L, 1962L, 1963L, 1964L, 1964L,
1964L, 1965L, 1966L, 1966L, 1966L, 1967L, 1968L, 1969L, 1969L,
1969L, 1971L, 1971L, 1971L, 1971L, 1971L, 1971L, 1971L, 1971L,
1972L, 1972L, 1973L, 1974L, 1974L, 1974L, 1974L, 1974L, 1974L,
1975L, 1975L, 1975L, 1975L, 1976L, 1976L, 1976L, 1976L, 1976L,
1977L, 1978L, 1979L, 1979L, 1980L, 1980L, 1980L, 1981L, 1981L,
1981L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L,
1983L, 1983L, 1984L, 1984L, 1984L, 1984L, 1984L, 1985L, 1985L,
1985L, 1985L, 1985L, 1986L, 1986L, 1986L, 1987L, 1987L, 1987L,
1988L, 1988L, 1988L, 1988L, 1989L, 1989L, 1989L, 1989L, 1989L,
1989L, 1989L, 1989L, 1989L, 1990L, 1990L, 1990L, 1990L, 1990L,
1990L, 1990L, 1991L, 1991L, 1991L, 1991L, 1991L, 1991L, 1992L,
1992L, 1992L, 1992L, 1992L, 1992L, 1992L, 1993L, 1993L, 1993L,
1993L, 1993L, 1993L, 1994L, 1994L, 1994L, 1994L, 1994L, 1994L,
1994L, 1994L, 1995L, 1995L, 1995L, 1995L, 1995L, 1995L, 1996L,
1996L, 1996L, 1996L, 1996L, 1996L, 1996L, 1997L, 1997L, 1997L,
1997L, 1998L, 1998L, 1998L, 1998L, 1998L, 1998L, 1998L, 1999L,
1999L, 1999L, 1999L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L,
2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2001L, 2001L, 2001L,
2001L, 2001L, 2002L, 2002L, 2002L, 2002L, 2003L, 2003L, 2003L,
2004L, 2004L, 2004L, 2004L, 2004L, 2004L, 2004L, 2004L, 2004L,
2004L, 2005L, 2005L, 2005L, 2005L, 2005L, 2005L, 2005L, 2005L,
2005L, 2005L, 2005L, 2005L, 2005L, 2006L, 2006L, 2006L, 2006L,
2006L, 2006L, 2006L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L,
2007L, 2007L, 2007L, 2007L, 2008L, 2008L, 2008L, 2008L, 2008L,
2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2010L, 2010L, 2010L,
2010L, 2010L, 2010L, 2010L, 2010L, 2010L, 2010L, 2011L, 2011L,
2011L, 2011L, 2011L, 2011L, 2011L, 2011L, 2011L, 2011L, 2011L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2013L, 2013L, 2013L,
2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2017L, 2017L, 2018L, 2018L, 2018L, 2018L, 2018L,
2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2019L, 2019L,
2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2020L,
2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L,
2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2021L, 2021L,
2021L, 2021L, 2021L, 2021L, 2021L, 2021L, 2021L, 2021L, 2021L,
2021L, 2021L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L,
2022L, 2023L, 2023L, 2023L, 2023L, 2023L, 2023L, 2023L, NA),
outcome = c(1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L,
2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L,
2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L
)), class = "data.frame", row.names = c(NA, -402L))
Haven't tried anything other than base R and ggplot2
Solution
If base R isn't a requirement, you can do this with ggplot2 by specifying fill=outcome in the aesthetic definitions and using position="stack" in the histogram geometry:
output
library(dplyr)
library(ggplot2)
Confirmed_Unprovoked_Attacks_ALL %>%
mutate(outcome = factor(outcome, levels=1:2, labels=c("Fatal", "Non-fatal"))) %>%
ggplot(aes(x=year, fill=outcome)) +
geom_histogram(position="stack", bins = 100) +
scale_x_continuous(limits=c(1850, 2050)) +
theme_classic() +
theme(legend.position="top") +
labs(x="Year", y="Count", fill="")
#> Warning: Removed 1 rows containing non-finite values (`stat_bin()`).
#> Warning: Removed 4 rows containing missing values (`geom_bar()`).
input
Confirmed_Unprovoked_Attacks_ALL <- structure(list(year = c(1876L, 1890L, 1890L, 1894L, 1907L, 1907L,
1909L, 1916L, 1916L, 1916L, 1922L, 1922L, 1926L, 1930L, 1934L,
1935L, 1935L, 1936L, 1936L, 1936L, 1937L, 1937L, 1950L, 1950L,
1951L, 1951L, 1952L, 1953L, 1954L, 1955L, 1955L, 1956L, 1956L,
1956L, 1956L, 1957L, 1957L, 1959L, 1959L, 1960L, 1960L, 1960L,
1960L, 1960L, 1961L, 1961L, 1962L, 1962L, 1963L, 1964L, 1964L,
1964L, 1965L, 1966L, 1966L, 1966L, 1967L, 1968L, 1969L, 1969L,
1969L, 1971L, 1971L, 1971L, 1971L, 1971L, 1971L, 1971L, 1971L,
1972L, 1972L, 1973L, 1974L, 1974L, 1974L, 1974L, 1974L, 1974L,
1975L, 1975L, 1975L, 1975L, 1976L, 1976L, 1976L, 1976L, 1976L,
1977L, 1978L, 1979L, 1979L, 1980L, 1980L, 1980L, 1981L, 1981L,
1981L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L,
1983L, 1983L, 1984L, 1984L, 1984L, 1984L, 1984L, 1985L, 1985L,
1985L, 1985L, 1985L, 1986L, 1986L, 1986L, 1987L, 1987L, 1987L,
1988L, 1988L, 1988L, 1988L, 1989L, 1989L, 1989L, 1989L, 1989L,
1989L, 1989L, 1989L, 1989L, 1990L, 1990L, 1990L, 1990L, 1990L,
1990L, 1990L, 1991L, 1991L, 1991L, 1991L, 1991L, 1991L, 1992L,
1992L, 1992L, 1992L, 1992L, 1992L, 1992L, 1993L, 1993L, 1993L,
1993L, 1993L, 1993L, 1994L, 1994L, 1994L, 1994L, 1994L, 1994L,
1994L, 1994L, 1995L, 1995L, 1995L, 1995L, 1995L, 1995L, 1996L,
1996L, 1996L, 1996L, 1996L, 1996L, 1996L, 1997L, 1997L, 1997L,
1997L, 1998L, 1998L, 1998L, 1998L, 1998L, 1998L, 1998L, 1999L,
1999L, 1999L, 1999L, 2000L, 2000L, 2000L, 2000L, 2000L, 2000L,
2000L, 2000L, 2000L, 2000L, 2000L, 2000L, 2001L, 2001L, 2001L,
2001L, 2001L, 2002L, 2002L, 2002L, 2002L, 2003L, 2003L, 2003L,
2004L, 2004L, 2004L, 2004L, 2004L, 2004L, 2004L, 2004L, 2004L,
2004L, 2005L, 2005L, 2005L, 2005L, 2005L, 2005L, 2005L, 2005L,
2005L, 2005L, 2005L, 2005L, 2005L, 2006L, 2006L, 2006L, 2006L,
2006L, 2006L, 2006L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L,
2007L, 2007L, 2007L, 2007L, 2008L, 2008L, 2008L, 2008L, 2008L,
2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2010L, 2010L, 2010L,
2010L, 2010L, 2010L, 2010L, 2010L, 2010L, 2010L, 2011L, 2011L,
2011L, 2011L, 2011L, 2011L, 2011L, 2011L, 2011L, 2011L, 2011L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2013L, 2013L, 2013L,
2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2017L, 2017L, 2018L, 2018L, 2018L, 2018L, 2018L,
2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2019L, 2019L,
2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2019L, 2020L,
2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L,
2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2020L, 2021L, 2021L,
2021L, 2021L, 2021L, 2021L, 2021L, 2021L, 2021L, 2021L, 2021L,
2021L, 2021L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L,
2022L, 2023L, 2023L, 2023L, 2023L, 2023L, 2023L, 2023L, NA),
outcome = c(1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L,
2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L,
2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L
)), class = "data.frame", row.names = c(NA, -402L))