Changing colors in graph using Matplotlib to plot Pandas dataframe

Question

So I have a dataframe which I have plotted and looks great using the code below. The issue is that there are ~10 colors being used and repeated for multiple enteries in the dataframe so that it is impossible to distinguish one dataframe entry from 20 others.

I figure there must be some way to state 'use X color scheme and allow for 60 colors' but I dont know how when using a dataframe.

dataframe = pd.DataFrame(new_vals)
dataframe.plot(kind='bar',stacked=True,legend=False, ylim=(0,100),title='Taxonomic analysis of samples')

N = 29
ind = np.arange(N)
width = 0.35




plt.xlabel('Sample')
plt.ylabel('Percentage of assembly atrribted to each taxonomic group (%)')
plt.legend(loc="best", bbox_to_anchor=(1.0, 1.00))
plt.xticks(ind+width/2. - 0.2,('B11', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8', 'B9', 'C10', 'C11', 'C2', 'C3', 'C4', 'C5', 'C6', 'C7', 'C8', 'C9', 'D10', 'D11', 'D2', 'D3', 'D4', 'D5', 'D6', 'D7', 'D8', 'D9'))

Here is an example of my dataframe;

    Other   actinomyces alcanivorax alkaliphilus    bacillus    bacteroides candidatus phytoplasma  cyanothece  enterobacter    escherichia ... neisseria   paenibacillus   porphyromonas   prevotella  pseudoalteromonas   rothia  staphylococcus  streptococcus   streptomyces    veillonella
0   26.229808   5.198240    4.694513    0.047974    3.691476    0.792203    2.782495    2.018697    2.180294    0.453228    ... 1.677198    4.944483    0.458910    5.496815    2.910004    0.372430    0.599676    8.276785    1.992817    0.595257
1   24.395006   11.615767   1.995668    0.069200    5.750399    0.921047    1.248692    0.740260    0.967860    1.904479    ... 0.873587    1.316648    0.261579    4.954371    1.348089    2.405995    1.061885    18.200302   1.660959    5.382657
2   22.078940   5.772762    3.107776    0.070983    5.523827    1.428608    1.846615    1.218850    1.542251    1.656823    ... 0.986514    2.414715    0.617899    6.893698    2.014352    0.496304    1.056452    22.272679   1.470803    2.696270
3   33.438669   5.210649    0.043170    0.136277    7.108181    2.148167    0.071589    0.034340    0.073281    2.719497    ... 1.922939    0.111153    3.898990    6.426144    0.045960    4.365727    1.545480    17.170125   0.870670    3.480261
4   20.831026   3.001972    4.746576    0.034374    2.198009    0.677926    3.264413    2.524014    2.720162    0.563074    ... 1.167616    9.110402    0.358742    3.323339    3.180934    0.420669    0.408120    8.948355    1.856454    1.086865

Fabio Lamanna · Accepted Answer · 2015-10-13 13:05:53Z

3

IIUC you can generate a colormap of kcolors with a function like the following:

def colormapgenerator(N, cm=None):

    base = plt.cm.get_cmap(cm)
    color_list = base(np.linspace(0, 1, N))
    cm_name = base.name + str(N)
    return base.from_list(cm_name, color_list, N)

where cm is your desidered cmap (e.g. Blues, Reds etc), and N is the number of colors you need. Than try to add to your dataframe.plot() the following:

cmap=colormapgenerator(60, 'Reds')

Hope that helps.

answered Oct 13, 2015 at 13:05

Fabio Lamanna

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