X-Axis is incorrectly positioned in Seaborn
I have a multi-level index frame that I am trying to display in Seaborn. The plot shows thin, but the x-axis values are treated as text labels instead of actual x-values. The snippet below shows how the sample data is produced and processed:
>>> import numpy, pandas, seaborn
>>> from matplotlib import pyplot
>>> index = pandas.MultiIndex.from_product((list('abc'), [10**x for x in range(4)]), names=['letters', 'powers'])
>>> index
MultiIndex(levels=[['a', 'b', 'c'], [1, 10, 100, 1000]],
labels=[[0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2], [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3]],
names=['letters', 'powers'])
>>> df = pandas.DataFrame(numpy.random.randn(12, 2), index=index, columns=['x', 't'])
>>> df
x t
letters powers
a 1 1.764052 0.400157
10 0.978738 2.240893
100 1.867558 -0.977278
1000 0.950088 -0.151357
b 1 -0.103219 0.410599
10 0.144044 1.454274
100 0.761038 0.121675
1000 0.443863 0.333674
c 1 1.494079 -0.205158
10 0.313068 -0.854096
100 -2.552990 0.653619
1000 0.864436 -0.742165
>>> seaborn.factorplot(x='powers', y='t', hue='letters', data=df.reset_index())
>>> pyplot.show()
The plot shows:
However, the x-axis uses numeric values as text labels. I would like the x-axis to display an exponential progression as expected from values (i.e. 1000 should be 10 times farther from 100 than 100 should be 10). How can I fix this?
I suspect the multi-index is not relevant to the problem, but perhaps the data type it interprets is significant. A similar problem seems to be happening here: sea boxes at desired distances along the x axis . I don't think this is a duplicate, but if the community disagrees, I would appreciate a brief explanation on how to apply it to my case.
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factorplot
treats yours [1, 10, 100, 1000]
as categories (or factors). These are not seabed numbers - just labels. Therefore, they are evenly spaced (and internally they place these marks on a linear spaced scale of 0 to 3). A side effect of this is that it mimics a scaled log view that you might want to keep.
If I understand correctly what you are trying to do, this can be achieved without maritime use, but if it is a style, you can then import it and do something like this:
fig, ax = plt.subplots(figsize=(5,3))
for l in df.index.get_level_values(0).unique():
ax.plot(df.loc[l, 'x'], 'o-', label=l)
ax.legend(loc=0)
ax.set_xlim([-10, 1001])
ax.set_xticks(df.index.get_level_values(1).unique())
Which will create a graph like this:
And I'm not sure if this is really what you want, since the linear scale representation on the x axis makes the left side unreadable. The current chart is in the form of a scaled "log" axis, which appears to be more readable.
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