This has been asked before. In my case though, modifying x-axis ticks through the traditional manner is not yielding results.
I have a data frame that has over 12,000 observations and have used ggplot
to plot a nice time-series graph.
The problem here is the x-axis ticks. I can well convert the date
column to proper datetime
format but that will require additional code. I might as well just paste these ticks from 1998 to 2017 with 5 year gaps and that will do the job.
However, in the ggplot layer, setting the axis ticks is not working as expected. This is the full code:
plt = ggplot(wyoming_permit_dat, aes(x = 'date', y = 'Total'))
plt + geom_point() + geom_line(color = 'red', alpha = 0.50, size = 2.5) + \
theme(axis_text_x = element_text(angle = 45, hjust = 1),
title = 'Time-Series of Total Checks for Wyoming (1998-2017)',
axis_title_x = 'Period', axis_title_y = 'Total Checks') + \
scale_x_discrete(labels = ['1998', '2003', '2008', '2013', '2018'])
I might be going wrong at specifying the breaks
argument for scale_x_discrete
but doing that cramps up the whole graph and makes it look like it got crushed. Is there a way I could just modify these labels without performing date-time conversions?
So I'm trying to figure out how to translate from R myself. The best I've figured out so far is manually labeling the breaks and labels.
base = Batting_Salaries[Batting_Salaries['HR'] > 10]
gg = ggplot(base, aes('HR' ,'salary')) + geom_bar() + scale_x_continuous(limits
= (0,40), breaks = (0,10,20,30,40), labels = [10,20,30,40,50])
gg