Python & Pandas: Strange behavior when Pandas plot histogram to a specific ax

Question

I want to plot pandas histogram to an axis, but the behavior is really strange. I don't know what's wrong here.

fig1, ax1 = plt.subplots(figsize=(4,3))
fig2, ax2 = plt.subplots(figsize=(4,3))
fig3, ax3 = plt.subplots(figsize=(4,3))

# 1. This works
df['speed'].hist()

# 2. This doens't work
df['speed'].hist(ax=ax2)

# 3. This works
data = [1,2,3,5,6,2,3,4]
temp_df = pd.DataFrame(data)
temp_df.hist(ax=ax2)

The error jupyter notebook returns is:

---

AssertionError                            Traceback (most recent call last)
<ipython-input-46-d629de832772> in <module>()
      7 
      8 # This doens't work
----> 9 df['speed'].hist(ax=ax2)
     10 
     11 # # This works

D:\Anaconda2\lib\site-packages\pandas\tools\plotting.pyc in hist_series(self, by, ax, grid, xlabelsize, xrot, ylabelsize, yrot, figsize, bins, **kwds)
   2953             ax = fig.gca()
   2954         elif ax.get_figure() != fig:
-> 2955             raise AssertionError('passed axis not bound to passed figure')
   2956         values = self.dropna().values
   2957 

AssertionError: passed axis not bound to passed figure

The pandas source code is here:

https://github.com/pydata/pandas/blob/d38ee272f3060cb884f21f9f7d212efc5f7656a8/pandas/tools/plotting.py#L2913

Totally have no idea what's wrong with my code.

Answer 1

The problem is that pandas determines which is the active figure by using gcf() to get the "current figure". When you create several figures in a row, the "current figure" is the last one created. But you are trying to plot to an earlier one, which causes a mismatch.

However, as you can see on line 2954 of the source you linked to, pandas will look for an (undocumented) figure argument. So you can make it work by doing df['speed'].hist(ax=ax2, figure=fig2). A comment in the pandas source notes that this is a "hack until the plotting interface is a bit more unified", so I wouldn't rely on it for anything too critical.

The other solution is to not create a new figure until you're ready to use it. In your example above, you only use figure 2, so there's no need to create the others. Of course, that is a contrived example, but in a real-life situation, if you have code like this:

fig1, ax1 = plt.subplots(figsize=(4,3))
fig2, ax2 = plt.subplots(figsize=(4,3))
fig3, ax3 = plt.subplots(figsize=(4,3))

something.hist(ax=ax1)
something.hist(ax=ax2)
something.hist(ax=ax3)

You can change it to this:

fig1, ax1 = plt.subplots(figsize=(4,3))
something.hist(ax=ax1)

fig2, ax2 = plt.subplots(figsize=(4,3))
something.hist(ax=ax2)

fig3, ax3 = plt.subplots(figsize=(4,3))
something.hist(ax=ax3)

That is, put each section of plotting code right after the code that creates the figure for that plot.