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tickr

This is a small package to provide consistent tick marks for plotting ‘ggplot2’ figures. It provides breaks and labels for ‘ggplot2’ without requiring ‘ggplot2’ to be installed.

Installation

You can install the development version of tickr from GitHub:

# install.packages("remotes")
remotes::install_github("BenWilliams-NOAA/tickr")

Example

library(tickr)
library(ggplot2)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

Some basic examples of how to use the tickr package.

# Create a data.frame
df <- data.frame(year = 2000:2020,
                 spawning_biomass = rnorm(21,100, 0.25))

# explore tickr output
tickr(df, var=year)
#>    breaks labels
#> 1    2000   2000
#> 2    2001       
#> 3    2002       
#> 4    2003       
#> 5    2004       
#> 6    2005   2005
#> 7    2006       
#> 8    2007       
#> 9    2008       
#> 10   2009       
#> 11   2010   2010
#> 12   2011       
#> 13   2012       
#> 14   2013       
#> 15   2014       
#> 16   2015   2015
#> 17   2016       
#> 18   2017       
#> 19   2018       
#> 20   2019       
#> 21   2020   2020
tickr(df, var=year, by=2)
#>    breaks labels
#> 1    2000   2000
#> 2    2001       
#> 3    2002   2002
#> 4    2003       
#> 5    2004   2004
#> 6    2005       
#> 7    2006   2006
#> 8    2007       
#> 9    2008   2008
#> 10   2009       
#> 11   2010   2010
#> 12   2011       
#> 13   2012   2012
#> 14   2013       
#> 15   2014   2014
#> 16   2015       
#> 17   2016   2016
#> 18   2017       
#> 19   2018   2018
#> 20   2019       
#> 21   2020   2020
tickr(df, var=year, by=5, var_min = 1998, var_max = 2024, lab_start = 1998, lab_end = 2017)
#>    breaks labels
#> 1    1998   1998
#> 2    1999       
#> 3    2000       
#> 4    2001       
#> 5    2002       
#> 6    2003   2003
#> 7    2004       
#> 8    2005       
#> 9    2006       
#> 10   2007       
#> 11   2008   2008
#> 12   2009       
#> 13   2010       
#> 14   2011       
#> 15   2012       
#> 16   2013   2013
#> 17   2014       
#> 18   2015       
#> 19   2016       
#> 20   2017       
#> 21   2018       
#> 22   2019       
#> 23   2020       
#> 24   2021       
#> 25   2022       
#> 26   2023       
#> 27   2024
tickr(df, var=year, by=5, var_min = 1998, var_max = 2024, lab_start = 1998, lab_end = 2017)
#>    breaks labels
#> 1    1998   1998
#> 2    1999       
#> 3    2000       
#> 4    2001       
#> 5    2002       
#> 6    2003   2003
#> 7    2004       
#> 8    2005       
#> 9    2006       
#> 10   2007       
#> 11   2008   2008
#> 12   2009       
#> 13   2010       
#> 14   2011       
#> 15   2012       
#> 16   2013   2013
#> 17   2014       
#> 18   2015       
#> 19   2016       
#> 20   2017       
#> 21   2018       
#> 22   2019       
#> 23   2020       
#> 24   2021       
#> 25   2022       
#> 26   2023       
#> 27   2024

# explore plotting options
# default ggplot
ggplot(df, aes(year, spawning_biomass)) + 
  geom_line() +
  geom_point()


# a tick mark for every year
ggplot(df, aes(year, spawning_biomass)) + 
  geom_line() +
  geom_point() +
  scale_x_tickr(data=df, var=year)


# a tick mark for every year & label every 2nd year
ggplot(df, aes(year, spawning_biomass)) + 
  geom_line() +
  geom_point() +
  scale_x_tickr(data=df, var=year, by = 2)


# determine the years that are labeled
ggplot(df, aes(year, spawning_biomass)) + 
  geom_line() +
  geom_point() +
  scale_x_tickr(data=df, var=year, by = 5, 
                var_min = 1997, 
                var_max = 2024, 
                lab_start = 1997) 


# determine the years that are labeled
ggplot(df, aes(year, spawning_biomass)) + 
  geom_line() +
  geom_point() +
  scale_x_tickr(data=df, var=year, by = 2, 
                var_min = 2010, 
                lab_start = 2010)


# show future years
ggplot(df, aes(year, spawning_biomass)) + 
  geom_line() +
  geom_point() +
  scale_x_tickr(data=df, var=year, by = 5, 
                var_min = 2015, 
                var_max = 2026, 
                lab_start = 2015, 
                lab_end = 2026) +
  expand_limits(x = c(1998, 2026))

The same general approach is available for y axes as well.

df <- expand.grid(age = 1:10,
                 year = 2000:2009) %>% 
  dplyr::mutate(value = rnorm(100, 1, 1))

df %>% 
  ggplot(aes(year, age, size=value)) + 
  geom_point() +
  scale_size_area() +
  scale_x_tickr(data=df, var=year, by=2, var_max = 2012, lab_end = 2012) +
  scale_y_tickr(data=df, var=age, by=2) +
  expand_limits(y=0, x=2012)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.