Stacked bar plot for a DataFrame

Question

I have a below table in a DataFrame. I want to visualize it in a stacked bar plot.

Percentage	A	B	C	D	E	F
0%	10	20	50	60	100	90
10%	89	87	65	87	89	88
50%	87	876	89	978	6	0
100%	89	78	89	89	54	34

For the above table, I want to get the stacked bar chart with x-axis as columns A,B,C,D,E,F and y-axis as Percentage Counts.

For example, x-axis column A has stacked bar with 10, 89, 87, 89 for the percentages.

I want output to be like

Answer 1

Since you want dummy bars, you have to craft a dummy DataFrame:

tmp = df.set_index('Percentage').T
X = np.repeat(100/tmp.shape[1], tmp.shape[1])

ax = tmp.notna().mul(X, axis=1).plot.bar(stacked=True)
ax.legend(bbox_to_anchor=(1.0, 1.0))
ax.set_yticks(np.cumsum(X)-X[0]/2, tmp.columns)

for k, c in zip(tmp, ax.containers):
    ax.bar_label(c, labels=tmp[k], label_type='center')

Output:

[

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Original answer

Set percentage as index (set_index), transpose, and plot the stacked bars (plot.bar with stacked=True):

df.set_index('Percentage').T.plot.bar(stacked=True)

Output:

If you want to group by percentage, skip the transpose and use barh:

df.set_index('Percentage').plot.barh(stacked=True)

Output: