I'm currently struggeling with an odd displaying error. Seems like my ticks on the axes are only shown right, if they only consist of one number. Even when I manually set the ticks.
I'm using matplotlib. Here is an example figure:
My problem are the rectangles shown after or around the numbers.
Related
I tried to do a box plot with salary and loan. However its not showing even though the code is correct. And I tried with matplotlib plots, it doesnt work as well.
Here is the code
I want to make the plot smaller, so it can save some space in print. However, when I make it smaller, the grid will be too tight:
Honestly, I don't get it. Why can't matplotlib auto-detect that this image is too small that the lable should be with a bigger interval?
So, How can I make the grid more sparse, so the lables won't overlap with each other?
Additionally, the title will also collapse with the labels. I can set it manually, by plt.suptitle(title, y=1.08). So it will look better
But I'm wondering if there is anyway to do it automatically?
Note: I'm using seaborn, but I tried with pure matplotlib, same problem.
I'm looking for a way to have interactive "circular panning" with matplotlib: when
interactively moving the axes to the left or the right, I want the data
(and axes labels) to "wrap around". (An (silly) example application would
be e.g. plotting annual average temperatures, and wanting to look at
whether anything special is happening around New Year.)
Is there a simple way to achieve this?
I'm having two different figures with identical figsize which I embed in an latex ducment (picture).
How can I make that it does not missalign slightly in the way it currently is? (the right figure has larger axis)
I want to make a plot in matplotlib that is wide and short. I can manipulate the size of a plot as answered on this question.
However, the x-axis label disappears if the plot is not tall enough. I want to squeeze the plot more while keeping the axis label visible.
Is there a way to manipulate the size of the plot without getting rid of the axis label?
After you change the plot size, run tight_layout(). Note that this requires matplotlib v1.1 or newer. If you have an older version of matplotlib, you can run subplot_tool() or subplots_adjust to adjust the plot manually.