I am trying to create a boxplot for paired data and want to draw lines between each paired data. Something similar is possible in R using ggpaired.
Is there as way to do so using seaborn or matplotlib in python?
Thanks in advance
IB
Related
I am trying to create a scatter plot (see image with code), but keep getting this super compressed single dot as the plot. I was unsure if it was an issue with the code or the data, so any help appreciated :)
The graph in question + code
I like the way that qutip plots quantum objects and I would like to plot my regular arrays like this. Does someone know if they are using any particular library or how to replicate it?
Here is an image of what I mean:
I want to plot the objects like this
It can be found in this notebook:
https://nbviewer.jupyter.org/github/jrjohansson/qutip-lectures/blob/master/Lecture-0-Introduction-to-QuTiP.ipynb
Thank you :D
I was recently doing some EDA on a data set.I created a boxplot, a countplot and a violinplot using seaborn and created an image using matplotlib.
But the result is not very easy on the eye and looks very congested.
Is this normal? Any way to make it better ?
This is the image of the notebook
The answer depends on your problem:)
In my opinion, the spacing is not the problem, the aspect ratio is. Your individual plots don't have enough height. So try to change te aspect ratio and see if you like it better. So change the first line to:
plt.Figure(figsize=(8, 12)
for example.
To whom may it concern,
Is it possible to plot an exploratory variable versus the target in h2o? I want to know whether it is possible to carry out basic data exploration in h2o, or whether it is not designed for that.
Many thanks in advance,
Kere
the main plotting functionality for an H2O frame is for histograms (hist() in python and h2o.hist() in R).
Within Flow you can do basic data exploration if you import your dataframe, then click on inspect and then, next to the hyperlinked columns, you'll see a plot button which will let you get bar charts of counts for example and other plot types.
You can also easily convert single columns you want to plot into a pandas or R dataframe with
H2OFrame.as_data_frame() in python
as.data.frame.H2OFrame in R and then use the native python and R plotting methods
A very similar question, solved the same way: how to use 'extent' in matplotlib.pyplot.imshow
I have a list of geographical coordinates (a "tracklog") that describe a geographical trajectory. Also, I have the means of obtaining an image spanning the tracklog coverage, where I know the "geographical coordinates" of the corners of the image.
My plot currently looks like this (notice the ticks - x=longitudes, y=latitudes, in UTM, WGS84):
Then suppose I know the corner coordinates of the following image (or a version of it without the blue track), and would like to plot it SO THAT IT FITS THE COORDINATE SYSTEM of the plot.
How would I do it?
(as a side note, in case that matters, I plan to use tiles)
As per the comment of Joe Kington (waiting for his actual answer so that I can accept it), the following code works as expected, giving a pannable and zoomable fixed-aspect "georeferenced" tile over which I am able to plot tracklogs:
import matplotlib.pyplot as plt
import Image
import numpy
imarray = numpy.asarray(Image.open('map.jpg'))
plt.plot([0,1], [0,1], 'o', c='red', ms=20) ## some reference circles for debugging
plt.imshow(imarray, extent=[0,1,0,1]) ## some random map whose corners have known coordinates
plt.axis('equal')
plt.show()
There is really not much of an answer here, but if you are using matplotlib, and you geos-tuff, take a look at matplotlib.basemap.
By default all operations are done on UTM maps, but you can choose your own projection.
Take also a look on the list of good tutorials in http://www.geophysique.be, for example.