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importpandasaspdimportmatplotlib.pyplotaspltser_1=pd.Series(data=[1,2,2,3,3,4,4,4,4,5])ser_2=ser_1.iloc[1:]fig,axes=plt.subplots(1,4,figsize=(16,4))axes[0].hist(ser_1.values)axes[1].hist(ser_1)axes[2].hist(ser_2.values)axes[3].hist(ser_2)
This snippet correctly plots in the first three cases, but errors in the last case, saying (in the relevant part):
/venv/local/lib/python2.7/site-packages/matplotlib/axes/_axes.pycinhist(self,x,bins,range,normed,weights,cumulative,bottom,histtype,align,orientation,rwidth,log,color,label,stacked,**kwargs)5602# Massage 'x' for processing.5603# NOTE: Be sure any changes here is also done below to 'weights'->5604ifisinstance(x,np.ndarray)ornotiterable(x[0]):5605# TODO: support masked arrays;5606x=np.asarray(x)
(which then descends into a KeyError in the bowels of pandas).
So seems like the issue here is thatx[0] is being used to find the first element of the input data (which would work fine if the input data is anumpy.ndarray). But in this casex is apandas.Series and as a resultx[0] is an index lookup rather than a normal slice. This works fine onaxes[1] since in that case the histogrammed series includes0 in its index. However, onaxes[3], the histogrammed data no longer includes0 in the index and things fall apart.