In this example on how to create partial dependence plots, it is explained that the ticks on the x-axis are decile marks. However, the API does not tell how to active/deactivate them. I tried finding a way of removing those, but so far no success has been achieved.
I'd appreciate any help in removing the bottom ticks. Thank you!
The lines are attributes of the PartialDependenceDisplay returned by plot_partial_dependence. The attributes are called deciles_vlines_ (for vertical lines) and deciles_hlines_ for horizontal lines. If you don't want to show them you can set them to not be visible with e.g. plt.setp
import matplotlib.pyplot as plt
disp = plot_partial_dependence(...)
plt.setp(disp.deciles_vlines_, visible=False)
Related
I'm building a python application to keep track of the BTC values over time through a graph that updates in realtime; in the x axis there is time and in the y axis the value of the corresponding BTC. my problem is that at the beginning the BTC values in the y axis are correct as in the first figure, but after some data received, the graph decides to "zoom" and express all the data in a different notation, as in the second figure (open imgur link).
https://imgur.com/a/spogs9G
I tried these two lines of code but without success:
plt.autoscale(enable=False, axis='y')
ax.get_yaxis().get_major_formatter().set_scientific(False)
If it can help, i am using:
import matplotlib.pyplot as plt
import matplotlib.animation as animation
If you would like to see all or part of the code, please ask.
Thank you in advance.
Fix the y-axis by using (as an example):
ax.set_ylim(0,1000)
and define the lower and upper bound accordign to your problem.
ax.set_ylim(lower_bound,upper_bound)
I have a plot that looks like this (this is the famous Wine dataset):
As you can see, the x-axis labels overlap and thus I need to be rotated.
NB! I am not interested in rotating the x-ticks (as explained here), but the label text, i.e. alcohol, malic_acid, etc.
The logic of creating the plot is the following: I create a grid using axd = fig.subplot_mosaic(...) and then for the bottom plots I set the labels with axd[...].set_xlabel("something"). Would be great if set_xlabel would take a rotation parameter, but unfortunately that is not the case.
Based on the documentation set_xlabel accepts text arguments, of which rotation is one.
The example I used to test this is shown below, though .
import matplotlib.pyplot as plt
import numpy as np
plt.plot()
plt.gca().set_xlabel('Test', rotation='vertical')
Hello there!
I am trying to create a figure consisting of a chloropleth map and a bar plot in Matplotlib. To achieve this, i am using the Geopandas library alongside Pandas and Matplotlib. I've run into an interesting problem that i couldn't find any answer for on the internet. Here's the problem:
This link leads to an image that replicates the problem.
As it can be seen on the image above, the map on the top (generated by Geopandas) does not span the same width as the bar chart on the bottom. There is too much whitespace to the left and the right of the figure. I want to get rid of this whitespace and make the map fit horizontally on the space that is allocated to it. I am also leaving a code sample below for those who wish to recreate it:
fig = plt.figure(figsize = (25.60,14.40)) #Here, i am setting the overall figure size
ax_1 = fig.add_subplot(2,1,1) #This will be the map
istanbul_districts.plot(ax = ax_1,
edgecolor = "black",
alpha = 1,
color = "Red") #Istanbul_districts is a GeoDataFrame object.
ax_2 = fig.add_subplot(2,1,2)
labels = list(health.loc[:,"district_eng"].value_counts().sort_values(ascending = False).index)
from numpy import arange
bar_positions = arange(len(labels)) + 1
bar_heights = h_inst_per_district_eng.loc[:,"health_count"].values.astype(int)
ax_2.bar(bar_positions,bar_heights,
width = 0.7,
align = "center",
color = "blue") #This is a generic barplot from Matplotlib
I am leaving a second image that shows the end result of the code snippet above:
This link also leads to an image that replicates the problem.
It can be clearly seen above that the axes of the two subplots do not start and end on the same location. Perhaps that could be the problem? What can be done to make them the same size?
Thanks to all those answer for their time in advance!
Adding an explanation, since you have found one solution.
If you specify matplotlib figure with two axes in a way you did, you get the figure split in half. Both axes are the same. Let's say that the original ratio of the figure is 1:1, your axes will be both 1:2.
This arbitrary ratio is fine for a bar chart, which can be scaled to essentially any ratio. It does not matter much if it is horizontal or vertical (from a plotting perspective, not data-viz).
However, if you want your map to show correct non-distorted shapes, you can't just specify the aspect ratio. That just follows the data. So if you have a map, which bounding box has 1:1 ratio, you can't expect that it will fill the whole 1:2 axis. GeoPandas changes the aspect ratio to follow the map's ratio.
The reason why the first example leaves gaps on side and the "solution" does not is this. Because the leftover space is on top and on the bottom the axis, it is not shown in the solution. Because it is on sides in the issue, it just stays there. If you had your plots next to each other instead of above, it would be vice versa.
Hope it is clearer.
Hello again!
swatchai's comment set me up on the right track and i found the culprit. Simply adjusting the figsize to a value like (19,19) fixed the problem. I'd still be happy if anyone can explain exactly why this happens.
Here's what it looks like when the figsize is a square (19,19):
Thanks for your efforts!
sns.boxplot(data=df, width=0.5)
plt.title(f'Distribution of scores for initial and resubmission\
\nonly among students who resubmitted at all.\
\n(n = {df.shape[0]})')
I want to use a bigger font, and leave more space in the top white margin so that the title doesn't get crammed in. Surprisingly, I am totally unable to find the option despite some serious googling!
The basic problem you have is that the multi-line title is too tall, and is rendered "off the page".
A few options for you:
the least effort solution is probably to use tight_layout(). plt.tight_layout() manipulates the subplot locations and spacing so that labels, ticks and titles fit more nicely.
if this isn't enough, also look at plt.subplots_adjust() which gives you control over how much whitespace is used around one or more subfigures; you can modify just one aspect at at time, and all the other settings are left alone. In your case, you could use plt.subplots_adjust(top=0.8).
If you are generating a final figure for publication or similar, you might be aiming to tweak a lot to perfect it. In this case, you can precisely control the (sub)plot locations, using add_axes (see this example https://stackoverflow.com/a/17479417).
Here is an example, with a 6-line title for emphasis. The left panel shows the default - with half the title clipped off. The right panel has all measurements the same except the top; the middle has automatically removed whitespace on all sides.
import seaborn as sns
import numpy as np
import matplotlib.pyplot as plt
data = 55 + 5* np.random.randn(1000,) # some data
vlongtitle = "\n".join(["long title"]*6) # a 6-line title
# using tight_layout, all the margins are reduced
plt.figure()
sns.boxplot(data, width=0.5)
plt.title(vlongtitle)
plt.tight_layout()
# 2nd option, just edit one aspect.
plt.figure()
sns.boxplot(data, width=0.5)
plt.title(vlongtitle)
plt.subplots_adjust(top=0.72)
Disclaimer: I am very inexperienced using matplotlib and python in general.
Here is the figure I'm trying to make:
Using GridSpec works well for laying out the plots, but when I try to include a colorbar on the right of each row, it changes the size of the corresponding subplot. This seems to be a well known and unavoidable problem with GridSpec. So at the advice of this question: Matplotlib 2 Subplots, 1 Colorbar
I've decided to remake the whole plot using ImageGrid. Unfortunately the documentation only lists the options cbar_mode=[None|single|each] whereas I want 1 colobar per row. Is there a way to do this inside a single ImageGrid? or will I have to make 2 grids and deal with the nightmare of alignment.
What about the 5th plot at the bottom? Is there a way to include that in the image grid somehow?
The only way I can see this working is to somehow nest two ImageGrids into a GridSpec in a 1x3 column. this seems overly complicated and difficult so I don't want to build that script until I know its the right way to go.
Thanks for any help/advice!
Ok I figured it out. It seems ImageGrid uses subplot somehow inside it. So I was able to generate the following plot using something like
TopGrid = ImageGrid( fig, 311,
nrows_ncols=(1,2),
axes_pad=0,
share_all=True,
cbar_location="right",
cbar_mode="single",
cbar_size="3%",
cbar_pad=0.0,
cbar_set_cax=True
)
<Plotting commands for the top row of plots and colorbar>
BotGrid = ImageGrid( fig, 312,
nrows_ncols=(1,2),
axes_pad=0,
share_all=True,
cbar_location="right",
cbar_mode="single",
cbar_size="3%",
cbar_pad=0.0,
)
<Plotting commands for bottom row . . .>
StemPlot = plt.subplot(313)
<plotting commands for bottom stem plot>
EDIT: the whitespace in the color plots is intentional, not some artifact from adding the colorbars