Color problems with pandas matplotlib - graph colors are inconsistent

Question

I have graphs with just 3 colors - Green, Red, Grey for values A, B, C. The application uses group by and value counts to get the cumulative count of A, B, and C across months and shows a donut chart, barh, and a bar chart. The colors shift from graph to graph - on one they A is green and the other graph with the same data shows A as red.

Simple fix, right?

def color_for_label(label):
    xlate = {'A': 'green',
             'B': 'red',
             'C': 'grey',
             }
    return [xlate[x] for x in label]


chart = gb.unstack(level=-1)
               .plot.barh(color=color_for_label(gb.index[0:2].names), 
                width=.50,
                stacked=True, 
                legend=None)

The data returns an index sometimes and a multiindex other times. It chokes on and but works on

The colors are constant Red/Green/Grey that always go with the values A/B/C.

I've tried checking datatypes and try/except structures, but both got too complex quickly. Anyone got a simple solution to share?

Lets use the data from this example pandas pivot table to stacked bar chart

df.assign(count =1 ).groupby(['battle_type']).count().plot.barh(stacked=True)

and (latter preferred - I'm not loving the groupby inconsistencies)

df.pivot_table(index='battle_type', columns='attacker_outcome', aggfunc='size').plot.barh(stacked=True)

both get me

I have a 3rd value, "Tie" in my example of A, B, C above, but lets ignore that for the moment.

I want to make sure that win is always green, lose is red, Tie is grey.

so I have my simple function

def color_for_label(label):
    xlate = {'win': 'green',
             'lose': 'red',
             'Tie': 'grey',
             }
return xlate[label]

so I add

....plot.barh(stacked=True, color=color_for_label(**label**))

And here I'm stuck - what do I set label to so that win is always green, lose is red and tie is grey?

You probably need to make sure the index is in the same order for each of your plot, and/or use matplotlib directly to give you more flexibility. I cannot help more without a Minimal, Complete, and Verifiable example. Provide mock-up data. In particular, refer to How to make good reproducible pandas examples — Diziet Asahi
– Diziet Asahi, Commented Feb 25, 2019 at 8:09

Josh Friedlander · Accepted Answer · 2019-02-26 16:18:58Z

1

Got it!

First, translate colors for the new example

def color_for_label(label):
    xlate = {'win': 'green',
             'loss': 'red',
             'tie': 'grey',
             }
    return [xlate[x] for x in label]

Then break it into two lines.

# create a dataframe
gb = df.pivot_table(index='battle_type', columns='attacker_outcome', aggfunc='size')

# pass the dataframe column values
gb.plot.barh(stacked=True, color=color_for_label(gb.columns.values))

edited Feb 26, 2019 at 16:18

Josh Friedlander

11.8k7 gold badges42 silver badges89 bronze badges

answered Feb 26, 2019 at 16:09

Harvey

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1 Comment

Harvey Over a year ago

see medium.com/dunder-data/… for additional info on why I switched to pivottable

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