In the case of large number of labels, there are not enough colors for drawing all the density matrices (get an error: plt.rcParams['axes.prop_cycle'].by_key()['color'][j] list index out of range). This change enables to manually input a list of colors to the JoyPy function, in the length of the labels (all(len(g) == len(color) for g in data)).

Hi @sbebo, Thanks very much for the fantastic module. I encountered a strange behaviour when trying to control figsize and overlap, which I assume is a bug. Here's a minimum code example:

# load modules and create a list of random data
import numpy as np
import joypy as jp

dist_list = []
for i in range(20):
    dist_list.append(np.random.normal(loc=np.random.random(), size=100))

With these arguments the plot is created normally:

fig, ax = jp.joyplot(dist_list, overlap=1, figsize=(8,3.3))
fig.show()

But for any height value of figsize that is higher than 3.3 in this case, all density plots appear extremely flattened, and changing the overlap has no effect at all:

fig, ax = jp.joyplot(dist_list, overlap=1, figsize=(8,3.4))
fig.show()

I noticed this when working on some larger data, and the "threshold" of this sudden change was at a different value for the height of figsize Is there a way to have a larger figure but prevent this from happening? Thanks!

If you create a joyplot, and then subsequently set the xlimits by calling matplotlib.pyplot.xlim(xmin, xmax), the x-axis labels shift but the data does not shift to reflect the new x range.

This can easily lead to incorrectly plotted data because no warning is given -- the axis labels just stop reflecting the actual data.

For instance, below is the exact same data plotted with joyplot, but in the first case there was a subsequent call to xlim to set a narrower xrange and in the second case there was not. As you can see, the xticks shifted but not the data.

I'm guessing the preferred way to set the xlimits is instead via the xrange parameter of joyplot, but I still worry the behavior described in this issue could easily lead to incorrect plots.

I saw the other import error in the solved issues, but this one is different. I'm using Pandas 0.20.3

File "myscript.py", line 17, in <module> import joypy File "/home/user/anaconda2/lib/python2.7/site-packages/joypy/init.py", line 1, in from .joyplot import joyplot, plot_density, _joyplot File "/home/user/anaconda2/lib/python2.7/site-packages/joypy/joyplot.py", line 221 raise ValueError("At least a column/group haNo numeric values found. Joyplot requires at least a numeric column/group.")

Hi,

I saw #17 explaining how to use kind="values and x_range in order to use aggregated data, but I'm finding it hard to combine this functionality with setting a specific column for output. I've got a dataset with a set of locations (lat & long) with measurements taken at each point giving a numerical value.

     lat        long        val

    001.012    001.01        11

    001.431    004.49        25

    001.769    008.72        04

    002.100    001.32        03

    002.504    003.49        17

    ...

(rubbish formatting but it gives you the right idea)

I've binned the y-values (lat) using pd.cut to give a lat_bins column and plotted this using:

fig, axes = jp.joyplot(df, by="lat_bins", column="long")

But what I'd like to have is something like:

fig, axes = jp.joyplot(df, by="lat_bins", column="long", kind="values", x_range=<some range>))

This displays a plot without any data; and no error appears when running the code so I don't know what to fix. The goal is to have a plot at each latitude showing the distribution according to longitude. (i.e., the dataset shown above would have the first layer showing 11 - 25 - 4 going across from 001 to 008 lat.

I created this joyplot below

However, for every one of the 20 teams on the y-axis, I want to colour them according to a Pandas dataframe column which contains a total value for every team. I was wondering if the colourmap could be customised to colour the plots according to a third data variable - either a Pandas Series, numpy array, or something similar. So for my dataframe the Total would look like this:

   Team     Total
Angers      356
Monaco      452
PSG         501
Lyon        369

Here's what works as expected:

fig, axes = joypy.joyplot(df, by="Team", column="Minute", figsize =(10,16), x_range = [0,94], linewidth = 1,
legend=False, colormap = color ,  title= "When do teams in Ligue 1 take their shots?")

Here are a few solutions I tried and failed at. Firstly, I created a colormap for the entire series depending on the Total data using this -

norm = plt.Normalize(group_df["Total"].min(), group_df["Total"].max())
cmap = plt.cm.viridis
sm = matplotlib.cm.ScalarMappable(cmap=cmap, norm=norm)
ar = np.array(group_df["Total"])
Cm = cmap(norm(ar))
sm.set_array([])

1 - Passing the customised colourmap in the function

fig, axes = joypy.joyplot(df, by="Team", column="Minute", figsize =(10,16), x_range = [0,94], linewidth = 1,
legend=False, colormap = Cm ,  title= "When do teams in Ligue 1 take their shots?")

2 - Passing the array of RGBA tuples to the colour

color = np.array(tuple(map(tuple,Cm)))
fig, axes = joypy.joyplot(df, by="Team", column="Minute", figsize =(10,16), x_range = [0,94], linewidth = 1,
legend=False, color = color ,  title= "When do teams in Ligue 1 take their shots?")

3 - Using the axes handles to set_facecolor - I saw this here

for col, ax in zip(Cm, axes):
        ax.patch.set_facecolor(col)

1 and 2 threw up an invalid RGBA argument and Assertion Error respectively. 3 had no error but the change was not reflected in the resulting plot. All I could gather is that currently, there's a no way to pass a list of colors (with a size similar to the grouped y-axis) or a customised colormap. If that's true, does there exist a work-around which I could implement? Or could a new feature be added?

Is there a way to get the y values of each subplot? I would like to plot several vertical lines corresponding to different quantities (for example, mean) and would like the line to go from the bottom of the plot up to the "top edge" of the plot (i.e. the y value).

For example, in the plot below I wanted to plot the mean but the vertical overshoots to plot (because I plotted until y=1)

Hi, I have a question about Y labels and believe this functionality exists, but I cannot get it right. E.g.: I can put Y axis labels on every subplot something like this:

fig, axes = joyploy(...)
for ax in axes:
    ax.set_ylabel("mylab")

This creates a label for every density plot. Can I somehow add a "global" Y axis label, instead of a Y axis label for every subplot. I suppose I can do that by providing an ax argument to joyploy, but it does not seem to work.

Thanks for your help, Simon

I'm trying to make a joyplot and when I set colormap=cm.autumn_r , my plot only uses the first color in the colormap. I wanted to use cm.tab20c and I eventually got it working by hacking the _get_color function to return colormap(i % len(colormap.colors)) . I don't think this is the right general solution but I'm not sure what to fix before submitting a pull request. Any ideas what might be going wrong? I think there might also be some weird interaction between gradient and named-color colormaps too.

Also, this package is amazing! Thank you so much for putting it together.

If you enter the name of a column which corresponds to non-numeric data, the error message given is:

~/miniconda3/lib/python3.6/site-packages/joypy/joyplot.py in _joyplot(data, grid, labels, sublabels, xlabels, xlabelsize, xrot, ylabelsize, yrot, ax, figsize, hist, bins, fade, xlim, ylim, fill, linecolor, overlap, background, range_style, x_range, tails, title, legend, loc, colormap, color, **kwargs)
    352     else:
    353         global_x_range = _x_range(x_range, 0.0)
--> 354     global_x_min, global_x_max = min(global_x_range), max(global_x_range)
    355 
    356     # Each plot will have its own axis

ValueError: min() arg is an empty sequence

This was encountered when trying to make plots of datetime values. The error message is not informative that the error is due to datetime not being a numeric type. Perhaps in _grouped_df_to_standard, when you check if the column is numeric, you can throw a warning or error if there are no numeric columns returned.

Hi,

The latest tag on github here is still 0.2.2 whilst the version has progressed to 0.2.5. Actually, I maintain this package in debian, and we take the source package from github (not pypi for several reasons) and hence it'd be very helpful if you could propagate the missing tag(s) (at least the latest one)

Could you please push the relevant tag?

=============================================================================================

CC: @leotac

Hi, I tried to plot a table with joypy with hist=True and "color" being a list of colors and got an error from matplotlib (v3.6.0).

Error message:

"ValueError: The 'color' keyword argument must have one color per dataset, but 1 datasets and 2 colors were provided"

How to reproduce:

import numpy as np
import pandas as pd
import joypy

table = pd.DataFrame({'one':np.random.randn(1000), 'two': 
np.random.randn(1000) + 5})

joypy.joyplot(table, color=['skyblue', 'fuchsia'], hist=True)

Hi!

I'm using joyplot with raw data (loving it so far). Attached are two figures I've produced. I would like to pass the axis generated from the first one as an argument into the second, in order to plot them on the same figure. However, I get the error below. Is there an easy work-around, without putting everything into dataframes?

Is it possible to inverse the plot eg:

Above is plotted by Target Field and each predictors on same line, if there are many features the plot looks too clustered.

Is it possible to split plot by predictors and each line showing target distribution, like the ggridges in R

ggplot(gather.data.train,aes(y = variable, fill = Target, x = value, alpha=0.4)) +  geom_density_ridges(scale = 5)

Thanks

I'd like to add a plot, side-by-side the joyplot, showing all of the distributions on one plot. I am successful at doing that, but something is weird with the xticks. I've been looking through the code at how the xticks are set and I don't see why what is in your package would be wrong.

The problem can be seen in the figure below. It looks like the xticks are being set relative to the figure size and not the last axes instance. Would you happen to know what's going on here? Because I sure don't. Any thoughts would be appreciated.

The figure:

The code:

from scipy.stats import gaussian_kde
import numpy as np
import pandas as pd
from sklearn import datasets

import joypy
import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.colors import rgb2hex

iris = datasets.load_iris()
df=pd.DataFrame(iris.data,columns=iris.feature_names)

fig = plt.figure(dpi=300)
gs = fig.add_gridspec(nrows=4, ncols=2)

ax1 = fig.add_subplot(gs[0, 0])
ax2 = fig.add_subplot(gs[1, 0])
ax3 = fig.add_subplot(gs[2, 0])
ax4 = fig.add_subplot(gs[3, 0])

ax5 = fig.add_subplot(gs[:, 1])

axes = [ax1, ax2, ax3, ax4]
joypy.joyplot(df, ax=axes, colormap=cm.autumn_r, linewidth=0.5)

limits = ax1.get_xlim()
x = np.arange(limits[0], limits[1], 0.01)
ncols = len(df.columns)

for i, (col, vals) in enumerate(df.items()):
    gkde = gaussian_kde(vals, bw_method=None)
    y = gkde.evaluate(x)
    ax5.plot(x, y, lw=0.5, color='k')
    ax5.fill_between(x, y, color=rgb2hex(cm.autumn_r(i / ncols)))