Python Pandas plot multiindex specify x and y

Question

Below is an example DataFrame.

           joaquin     manolo
xx 0  0.000000e+00  44.000000
   1  1.570796e+00  52.250000
   2  3.141593e+00  60.500000
   3  4.712389e+00  68.750000
   4  6.283185e+00  77.000000
yy 0  0.000000e+00  37.841896
   1  2.078796e+00  39.560399
   2  5.292179e-17  41.026434
   3 -8.983291e-02  42.304767
   4 -4.573916e-18  43.438054

As you can see, the row index has two levels, ['xx', 'yy'] and [0, 1, 2, 3, 4]. I want to call DataFrame.plot() in such a way that it will produce two subplots, one for joaquin and one for manolo, and where I can specify to use data.loc["xx", :] for the domain data and to use data.loc["yy", :] for the ordinate data. In addition, I want the option to supply the subplots on which the plots should be drawn, in a list (or array) of matplotlib.axes._subplots.AxesSubplot instances, such as those that can be returned by the DataFrame.hist() method. How can this be done?

Generating the data above

Just in case you're wondering, below is the code I used to generate the data. If there is an easier way to generate this data, I'd be very interested to know as a side-note.

joaquin_dict = {}
xx_joaquin = numpy.linspace(0, 2*numpy.pi, 5)
yy_joaquin = 10 * numpy.sin(xx_joaquin) * numpy.exp(-xx_joaquin)
for i in range(len(xx_joaquin)):
    joaquin_dict[("xx", i)] = xx_joaquin[i]
    joaquin_dict[("yy", i)] = yy_joaquin[i]

manolo_dict = {}
xx_manolo = numpy.linspace(44, 77, 5)
yy_manolo = 10 * numpy.log(xx_manolo)
for i in range(len(xx_manolo)):
    manolo_dict[("xx", i)] = xx_manolo[i]
    manolo_dict[("yy", i)] = yy_manolo[i]

data_dict = {"joaquin": joaquin_dict, "manolo": manolo_dict}
data = pandas.DataFrame.from_dict(data_dict)

HYRY · Accepted Answer · 2016-09-30 11:57:43Z

3

Just use a for loop:

fig, axes = pl.subplots(1, 2)
for ax, col in zip(axes, data.columns):
    data[col].unstack(0).plot(x="xx", y="yy", ax=ax, title=col)

output:

answered Sep 30, 2016 at 11:57

HYRY

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