A few legends on Pandas df.plot subplots?

Question

Earlier, I asked a question about how to build various columns from pandas data in separate subheadings here: Split several rows on subheadings using pandas df.plot , and got an excellent answer. Now I'm trying to make the most of the space on the plot, and the legend turns out to be a problem. What I would like to do is put 3 or 4 episodes on one legend, and the rest on another, so that I can put everyone in a corner where they will fit in well.

I tried using the methods described for matplotlib shown here:

from matplotlib.pyplot import * p1, = plot([1,2,3], label="test1") p2, = plot([3,2,1], label="test2") l1 = legend([p1], ["Label 1"], loc=1) l2 = legend([p2], ["Label 2"], loc=4) # this removes l1 from the axes. gca().add_artist(l1) # add l1 as a separate artist to the axes show() 

but I get problems associated with either using pandas df.plot or trying to implement on a subtitle. Here is what I tried:

 f, (ax1, ax2) = plt.subplots(ncols = 2) p1 = dfcomb.iloc[:,:3].plot(ax=ax1, figsize=(14,5)) p2 = dfcomb.iloc[:,3:6].plot(ax=ax1, figsize=(14,5)) l1 = ax1.legend([p1], ["Label 1"], loc=1) l2 = ax1.legend([p2], ["Label 2"], loc=4) # this removes l1 from the axes. gca().add_artist(l1) # add l1 as a separate artist to the axes 

and here is what I get:

 --------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-108-d3206d8ce17d> in <module>() 15 l1 = ax1.legend([p1], ["Label 1"], loc=1) 16 l2 = ax1.legend([p2], ["Label 2"], loc=4) # this removes l1 from the axes. ---> 17 gca().add_artist(l1) 18 19 ax1.set_xlabel('Suction (cm)') C:\Anaconda\lib\site-packages\matplotlib\axes\_base.pyc in add_artist(self, a) 1646 Returns the artist. 1647 """ -> 1648 a.axes = self 1649 self.artists.append(a) 1650 self._set_artist_props(a) C:\Anaconda\lib\site-packages\matplotlib\artist.pyc in axes(self, new_axes) 235 if (new_axes is not None and 236 (self._axes is not None and new_axes != self._axes)): --> 237 raise ValueError("Can not reset the axes. You are " 238 "probably trying to re-use an artist " 239 "in more than one Axes which is not " ValueError: Can not reset the axes. You are probably trying to re-use an artist in more than one Axes which is not supported 

Does anyone have a workaround?

Answer 1

You are ambushed by a false assumption about the nature of gca() . I was also surprised, so I decided to add an answer (otherwise we mostly talk about the typo problem). I also note that the problem has nothing to do with pandas.

Here is a minimal example reproducing your problem without pandas:

 import matplotlib.pyplot as plt f, (ax1, ax2) = plt.subplots(ncols = 2) p1, = ax1.plot([1,2,3], label="test1") p2, = ax1.plot([3,2,1], label="test2") l1 = ax1.legend([p1], ["Label 1"], loc=1) l2 = ax1.legend([p2], ["Label 2"], loc=4) # this removes l1 from the axes. plt.gca().add_artist(l1) 

So what's the problem? Take a look at the error message:

ValueError: Cannot reset axes. Perhaps you are trying to reuse the artist in several axes, which is not supported

(my emphasis). Take a look:

 >>> ax1 <matplotlib.axes._subplots.AxesSubplot at 0x7fd83abf7e10> >>> ax2 <matplotlib.axes._subplots.AxesSubplot at 0x7fd83a992850> >>> plt.gca() <matplotlib.axes._subplots.AxesSubplot at 0x7fd83a992850> 

The problem is that although you are working with ax1 , the "graphic current axes", also called gca() point to ax2 , Axes created last.

The solution is now simple: be explicit with a redraw call (remember that explicit is better than implicit):

 import matplotlib.pyplot as plt f, (ax1, ax2) = plt.subplots(ncols = 2) p1, = ax1.plot([1,2,3], label="test1") p2, = ax1.plot([3,2,1], label="test2") l1 = ax1.legend([p1], ["Label 1"], loc=1) l2 = ax1.legend([p2], ["Label 2"], loc=4) # this removes l1 from the axes. ax1.add_artist(l1) # <-- just change here, refer to ax1 explicitly 

And it's live!

---

If you really want to use the df.plot ( df.plot function) instead of managing the df.plot you df.plot , you will have to do a bit more work. Unfortunately, df.plot returns the Axes object it builds (and not the list of line features included in the graph), so we need to look at the Axes children to find the graphs. The above example using data frames:

 import pandas as pd import matplotlib import matplotlib.pyplot as plt # example input df1 = pd.DataFrame({'test1': [1,2,3]}) df2 = pd.DataFrame({'test2': [3,2,1]}) f, (ax1, ax2) = plt.subplots(ncols = 2) # disable automatic legends in order two have two separate legends df1.plot(ax=ax1, legend=False) df2.plot(ax=ax1, legend=False) # ugly hack to grab the children of the created Axes p1,p2 = [child for child in ax1.get_children() if isinstance(child, matplotlib.lines.Line2D)] # untangling the plots will be harder the more plots there are in the Axes l1 = ax1.legend([p1], df1.columns, loc=1) l2 = ax1.legend([p2], df2.columns, loc=4) # this removes l1 from the axes. ax1.add_artist(l1) # <-- just change here, refer to ax1 explicitly