Harshavardhan Ramanna - 1 year ago 105
Python Question

# How can I add a constant percentage to each wedge of a pie chart using matplotlib

Code snippet looks like this

``````#df is dataframe with 6 rows, with each row index being the label of the sector
plt.pie(df.iloc[:,0], labels= df.index) #plot the first column of dataframe as a pie chart
``````

It generates a pie chart like this:

Pie Chart with the 6 sectors.

As you can see, the sectors kitchen & entertainment are very small. I want to make each sector have a minimum value of 10 degree (1/36 %).

This would effectively mean fitting the data over 300 degrees (10 degree to each sector and we have 6 - Lighting, Entertainment, Kitchen, Cooling, Fridge, Others)

I want to make each sector have a minimum value of 10 degree

Solving this for the general case is difficult and requires further definition. This introduces a skew into the results, and to decide between different algorithms, you'd need to specify a metric defining how close is some skewed result to the original.

However, there is a very simple thing you can do which will guarantee your requirement. Say the length of your DataFrame is n, the sum of its elements is s, and you want the result to have no less than α (in your case, α = 1./36). If you would simply add some x to all elements, then the new sum would be

s + nx

Assuming that no element is negative, the smallest element would have weight at least x / (s + nx).

Solving for

x / (s + nx) = α

Gives

x = s α / (1 - αn).

So, if the Series you wish to pie-chart is `df.a`, you could do

``````x = max(df.a.sum() * alpha / (1 - alpha * len(df)), 0)
``````

and then plot instead `df.a + x`.

Example

``````df = pd.DataFrame({'a': [1, 2, 3, 40, 40, 50, 50, 500]})

x = max(df.a.sum() * alpha / (1 - alpha * len(df)), 0)
``````

You can check the smallest relative weight of `df.a + x`

``````(df.a + x).min() / (df.a + x).sum()
``````

is indeed greater than α.

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