I have a problem making histograms from pandas series objects and I can't understand why it does not work. The code has worked fine before but now it does not.
Here is a bit of my code (specifically, a pandas series object I'm trying to make a histogram of):
type(dfj2_MARKET1['VSPD2_perc'])
which outputs the result:
pandas.core.series.Series
Here's my plotting code:
fig, axes = plt.subplots(1, 7, figsize=(30,4))
axes[0].hist(dfj2_MARKET1['VSPD1_perc'],alpha=0.9, color='blue')
axes[0].grid(True)
axes[0].set_title(MARKET1 + ' 5-40 km / h')
Error message:
AttributeError Traceback (most recent call last)
<ipython-input-75-3810c361db30> in <module>()
1 fig, axes = plt.subplots(1, 7, figsize=(30,4))
2
----> 3 axes[1].hist(dfj2_MARKET1['VSPD2_perc'],alpha=0.9, color='blue')
4 axes[1].grid(True)
5 axes[1].set_xlabel('Time spent [%]')
C:\Python27\lib\site-packages\matplotlib\axes.pyc in hist(self, x, bins, range, normed, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, stacked, **kwargs)
8322 # this will automatically overwrite bins,
8323 # so that each histogram uses the same bins
-> 8324 m, bins = np.histogram(x[i], bins, weights=w[i], **hist_kwargs)
8325 m = m.astype(float) # causes problems later if it's an int
8326 if mlast is None:
C:\Python27\lib\site-packages\numpy\lib\function_base.pyc in histogram(a, bins, range, normed, weights, density)
158 if (mn > mx):
159 raise AttributeError(
--> 160 'max must be larger than min in range parameter.')
161
162 if not iterable(bins):
AttributeError: max must be larger than min in range parameter.
This error occurs among other things when you have NaN values in the Series. Could that be the case?
These NaN's are not handled well by the hist
function of matplotlib. For example:
s = pd.Series([1,2,3,2,2,3,5,2,3,2,np.nan])
fig, ax = plt.subplots()
ax.hist(s, alpha=0.9, color='blue')
produces the same error AttributeError: max must be larger than min in range parameter.
One option is eg to remove the NaN's before plotting. This will work:
ax.hist(s.dropna(), alpha=0.9, color='blue')
Another option is to use pandas hist
method on your series and providing the axes[0]
to the ax
keyword:
dfj2_MARKET1['VSPD1_perc'].hist(ax=axes[0], alpha=0.9, color='blue')