I have a matplotlib plot on which I found the coordinates of given points like this:
I am trying to find a way to add different axes on the same plot, and get the coordinates of the same points but according to the new axis system, like this:
I am very much a python beginner and I have been struggling with this. Is there a way to do that ?
I am trying to plot time series data in a kind of "climate stripes plot" using the package Altair.
The problem is that I do not know how to change the range in the legend to standardise all my plots with the same colour range and numbers in the legend. At the moment, each time I plot something the legend adapts to the range of the data.
I think the problem is with the "domain" property, maybe is not in the correct place ?
Thank you for your help :)
This is the code for the plot :
chart=alt.Chart(source).mark_rect().encode(
x=('day:O'),
y='subasins:N',
color=alt.Color('90%:Q',legend=alt.Legend(title='CH4'), bin=alt.Bin(maxbins=20),
scale=alt.Scale(scheme='blueorange'),domain=[1830,2000])
).properties(width=100).facet(column=alt.Column('month'))
chart.show()
Plots that I get now with different scales in the legend
You're using the right approach with domain, it just needs to be put inside alt.Scale:
scale=alt.Scale(scheme='blueorange', domain=[1830, 2000])
When you're using a bin transform, one way to ensure the scale is consistent is to specify the bin extent:
bin=alt.Bin(maxbins=20, extent=[1830, 2000])
I have a binned data of an x-axis n-length vector and 3 y-axis n-length vector for 3 different histograms on the same x-axis.
Now I want this kind of stacked bar plot or any thing similar as below.
The nearest I have found is Qtiplot (which is not python). It can generate exactly this kind of histogram plots. But it computes the histogram by itself and requires the actual data samples which are not present in my case (I only have the histogram itself).
Please note that I don't know python very well. So I don't have a clue from where I shall start, neither I am really in a mood to learn programming in python. I need this only to make a nice vector-graphics plot for my research thesis.
I have tagged python as I think python is the most obvious language. In case someone knows any better solution other than in python (but not Matlab, I cannot install that huge pile), I will thankfully add the proper tag.
Thanks in advance for any help.
use matplotlib package in python
import matplotlib.pyplot as plt
apple_weight=[3,3,3,10,10,1,1,1,4,4,4,4,7,7,7]
banana_weight=[3,3,3,10,10,1,1,1,4,4,4,4,7,7,7]
mango_weight=[3,3,3,10,10,1,1,1,4,4,4,4,7,7,7]
fig=plt.figure()
ax1=fig.add_subplot(311)
ax2=fig.add_subplot(312)
ax3=fig.add_subplot(313)
ax1.hist(apple_weight)
ax2.hist(banana_weight)
ax3.hist(mango_weight)
plt.show()
import matplotlib.pyplot as plt
apple_weight=[3,3,3,10,10,1,1,1,4,4,4,4,7,7,7]
banana_weight=[3,3,3,10,10,1,1,1,4,4,4,4,7,7,7]
mango_weight=[3,3,3,10,10,1,1,1,4,4,4,4,7,7,7]
fig=plt.figure()
ax1=fig.add_subplot(111)
ax2=ax1.twinx()
#only two y axes so the third list just add to either
ax1.hist(apple_weight)
ax2.hist(banana_weight)
ax1.hist(mango_weight)
plt.show()
I have data that occurs in an arrays at x(0:127), y(0:127), and z(0:98). For example, at the coordinates of x=23, y=27, and z=76 the data value might be 826. How can I create a 3d pcolorrmesh of these values to look similar to the link provided:
I don't think you can use pcolormesh for 3D plots. However look here for the official matplotlib tutorial on 3D plottting.
Is there any (simple or complex) way to recreate this plot in matplotlib?
I've tried plotting it using a scatter plot with two different x-values, while adding a small random number to it, but obviously it didn't produce the nice "ordered" effect seen above.
There's a package built on top of matplotlib called beeswarm that positions the points as requested.