Python Pandas Bar Chart - change color for specific bars

Question

I have some data in csv.

It has only one column and contents strings with soccer scores like "0:0","1:2",etc.

Then I building histogam with df[0].value_counts().plot(kind='bar').

What is the best way to change color only for bars with "draw" score (0:0, 1:1,...)?

I can add second column with '1' for draws and '0' for others, but don't understand how to use it as bar color.

I tried solution from another question here

df[0].value_counts().plot(kind='bar', color=(df[1] == 1).map({True: 'orange', False: 'blue'})) but got wrong coloring

wrong coloring, expecting orange "1:1"
example dataframe:

jezrael · Accepted Answer · 2020-02-05 13:23:57Z

2

Use numpy.where for test if match 1 column with Index.isin for array of colors passed to color parameter:

a = df[0].value_counts()
colors = np.where(a.index.isin(df.loc[df[1] == 1, 0].unique()), 'orange', 'blue')
a.plot(kind='bar', color=colors)

answered Feb 5, 2020 at 13:23

jezrael

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4 Comments

dad Over a year ago

Thank you, it works! Is there way to do it without numpy?

jezrael Over a year ago

if use panas, also use numpy, so if use pd.np.where instead np.where it working

jezrael Over a year ago

@dad or use colors = a.index.isin(df.loc[df[1] == 1, 0].unique()).map({True: 'orange', False: 'blue'})

jezrael Over a year ago

@dad or use colors = a.index.isin(df.loc[df[1] == 1, 0].unique()).to_series().map({True: 'orange', False: 'blue'}) if oldier pandas version

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