I'm using matplotlib to generate a (vertical) barchart. The problem is my labels are rather long. Is there any way to display them vertically, either in the bar or above it or below it?
Do you mean something like this:
>>> from matplotlib import *
>>> plot(xrange(10))
>>> yticks(xrange(10), rotation='vertical')
?
In general, to show any text in matplotlib with a vertical orientation, you can add the keyword rotation='vertical'.
For further options, you can look at help(matplotlib.pyplot.text)
The yticks function plots the ticks on the y axis; I am not sure whether you originally meant this or the ylabel function, but the procedure is alwasy the same, you have to add rotation='vertical'
Maybe you can also find useful the options 'verticalalignment' and 'horizontalalignment', which allows you to define how to align the text with respect to the ticks or the other elements.
In Jupyter Notebook you might use something like this
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
plt.xticks(rotation='vertical')
plt.plot(np.random.randn(100).cumsum())
or you can use:
plt.xticks(rotation=90)
Please check out this link:
https://python-graph-gallery.com/7-custom-barplot-layout/
import matplotlib.pyplot as plt
heights = [10, 20, 15]
bars = ['A_long', 'B_long', 'C_long']
y_pos = range(len(bars))
plt.bar(y_pos, heights)
# Rotation of the bars names
plt.xticks(y_pos, bars, rotation=90)
The result will be like this
Hopefully, it helps.
I would suggest looking at the matplotlib gallery. At least two of the examples seem to be relevant:
text_rotation.py for understanding how text layout works
barchart_demo2.py, an example of a bar chart with somewhat more complicated layout than the most basic example.
Related
graph
how do I make this graph infill all the square around it? (I colored the part that I want to take off in yellow, for reference)
Normally I use two methods to adjust axis limits depending on a situation.
When a graph is simple, axis.set_ylim(bottom, top) method is a quick way to directly change y-axis (you might know this already).
Another way is to use matplotlib.ticker. It gives you more utilities to adjust axis ticks in your graph.
https://matplotlib.org/3.1.1/gallery/ticks_and_spines/tick-formatters.html
I'm guessing you're using a list of strings to set yaxis tick labels. You may want to set locations (float numbers) and labels (string) of y-axis ticks separatedly. Then set the limits on locations like the following snippet.
import matplotlib.pyplot as plt
import matplotlib.ticker as mt
fig, ax = plt.subplots(1,1)
ax.plot([0,1,2], [0,1,2])
ax.yaxis.set_major_locator(mt.FixedLocator([0,1,2]))
ax.yaxis.set_major_formatter(mt.FixedFormatter(["String1", "String2", "String3"]))
ax.set_ylim(bottom=0, top=2)
It gives you this: generated figure
Try setting the min and max of your x and y axes.
I am trying to display a chart using matplotlib. But my labels are so big that they are overlapping each other. I want to show it cleanly no overlapping. How can I do that? I am now using below code:
import matplotlib.pyplot as plt
x = ['jdwdw723#gmail.com' ,'emcast.test10#gmail.com', 'pbChinaTester#clp.com']
y = [10,25,6]
plt.plot(x,y)
plt.xlabel("loginId")
plt.ylabel("times appeared in the data")
plt.title("loginId Graph")
plt.tight_layout()
plt.show()
I tried your example code, and it doesn't seem to be overlapping there. There are many possibilities. One, commonly used, is to rotate the labels.
You can do it like this:
plt.xticks(rotation=45)
There are more ideas in Changing the “tick frequency” on x or y axis in matplotlib? and in reducing number of plot ticks.
I created an example notebook here, feel free to duplicate and play with it.
I am currently creating a graph that that analyzes the correlation of absorption and concentration (Beer's law). While creating the graph, I've ran into a few problems, and I am now stuck. My plots are not showing up within my graph. Is it due to placement error? If possible, I would like to leave the ticks, labels, and title in the same (or similar format). Sorry in advance for the sloppiness, trying to get the function down before I make it pretty. But anyways, here is the code:
#importing matplotlib to create a graph
import matplotlib.pyplot as plt
#ploting out the points while labeling the graph
plt.plot([1.95E-06, 9.75E-06, 1.95E-05, 9.75E-05, 1.95E-04, 9.75E-04, 1.95E-
03],[0.2,0.4,0.6,0.8,1.0,1.2,1.4])
plt.xticks([1, 2, 3, 4, 5, 6, 7], [str('1.95E-03'), str('9.75E-04'),
str('1.95E-04'), str('9.75E-05'),str('1.95E-05'), str('9.75E-06'),
str('1.95E-06')])
plt.title('Red')
plt.ylabel('Absorption')
plt.xlabel('Concentration')
plt.grid(True)
plt.show()
Your xticks are completely out of the range where your data lives. Remove the line which sets the xticks and your plot is fine
import matplotlib.pyplot as plt
plt.plot([1.95E-06, 9.75E-06, 1.95E-05, 9.75E-05, 1.95E-04, 9.75E-04, 1.95E-03],
[0.2,0.4,0.6,0.8,1.0,1.2,1.4])
plt.title('Red')
plt.ylabel('Absorption')
plt.xlabel('Concentration')
plt.grid(True)
plt.show()
If you want to use your custom ticks, you need to set them in the data range, i.e. somewhere between 0 and 0.002 and not between 1 and 7.
Your data has x values well below 0.01, while your ticks start at 1, so your data will be to the left of the plot. I would suggest using a logarithmic x axis, just like the example below. This will also fix the problem with the x values being of different orders of magnitude. Note that I also put the tick strings in reverse order, assuming that you mistakenly wrote them the other way round. If not, please just go ahead and re-reverse them!
#importing matplotlib to create a graph
import matplotlib.pyplot as plt
x = [1.95e-06, 9.75e-06, 1.95e-05, 9.75e-05, 1.95e-04, 9.75e-04, 1.95e-03]
#ploting out the points while labeling the graph
plt.semilogx(x ,[0.2,0.4,0.6,0.8,1.0,1.2,1.4])
plt.xticks(x, [str('1.95E-03'), str('9.75E-04'), str('1.95E-04'), str('9.75E-05'),str('1.95E-05'), str('9.75E-06'), str('1.95E-06')], rotation=45)
plt.title('Red')
plt.ylabel('Absorption')
plt.xlabel('Concentration')
plt.grid(True)
plt.tight_layout()
plt.savefig('points.png')
plt.show()
The first argument to plt.xticks should be x-coords (not tick indexes).
I need to plot multiple sets of data on the same plot, and I use matplotlib.
For some of plots I use plt.plot() and for the others I use plt.errorbar(). But when I make a legend the ones created with plt.plot() appears first, no matter in which order I put them in the file (and zorder seems to have no effect on the position in the legend).
How can I give the order that I want in the legend, regardless of the way I plot the data?
You can adjust the order manually, by getting the legend handles and labels using ax.get_legend_handles_labels, and then reordering the resulting lists, and feeding them to ax.legend. Like so:
import matplotlib.pyplot as plt
import numpy as np
fig,ax = plt.subplots(1)
ax.plot(np.arange(5),np.arange(5),'bo-',label='plot1')
ax.errorbar(np.arange(5),np.arange(1,6),yerr=1,marker='s',color='g',label='errorbar')
ax.plot(np.arange(5),np.arange(2,7),'ro-',label='plot2')
handles,labels = ax.get_legend_handles_labels()
handles = [handles[0], handles[2], handles[1]]
labels = [labels[0], labels[2], labels[1]]
ax.legend(handles,labels,loc=2)
plt.show()
If I create a plot with matplotlib using the following code:
import numpy as np
from matplotlib import pyplot as plt
xx = np.arange(0,5, .5)
yy = np.random.random( len(xx) )
plt.plot(xx,yy)
plt.imshow()
I get a result that looks like the attached image. The problem is the
bottom-most y-tick label overlaps the left-most x-tick label. This
looks unprofessional. I was wondering if there was an automatic
way to delete the bottom-most y-tick label, so I don't have
the overlap problem. The fewer lines of code, the better.
In the ticker module there is a class called MaxNLocator that can take a prune kwarg.
Using that you can remove the first tick:
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
import numpy as np
xx = np.arange(0,5, .5)
yy = np.random.random( len(xx) )
plt.plot(xx,yy)
plt.gca().xaxis.set_major_locator(MaxNLocator(prune='lower'))
plt.show()
Result:
You can pad the ticks on the x-axis:
ax.tick_params(axis='x', pad=15)
Replace ax with plt.gca() if you haven't stored the variable ax for the current figure.
You can also pad both the axes removing the axis parameter.
A very elegant way to fix the overlapping problem is increasing the padding of the x- and y-tick labels (i.e. the distance to the axis). Leaving out the corner most label might not always be wanted. In my opinion, in general it looks nice if the labels are a little bit farther from the axis than given by the default configuration.
The padding can be changed via the matplotlibrc file or in your plot script by using the commands
import matplotlib as mpl
mpl.rcParams['xtick.major.pad'] = 8
mpl.rcParams['ytick.major.pad'] = 8
Most times, a padding of 6 is also sufficient.
This is answered in detail here. Basically, you use something like this:
plt.xticks([list of tick locations], [list of tick lables])