Sometimes, we want to bin data in Python with scipy or numpy.

In this article, we’ll look at how to bin data in Python with scipy or numpy.

How to bin data in Python with scipy or numpy?

To bin data in Python with scipy or numpy, we can use the linspace method to create the bins.

And then we call digitize to put the data into the bins`.

For instance, we write

import numpy
data = numpy.random.random(100)
bins = numpy.linspace(0, 1, 10)
digitized = numpy.digitize(data, bins)
bin_means = [data[digitized == i].mean() for i in range(1, len(bins))]

to create the bins with

bins = numpy.linspace(0, 1, 10)

We call linspace to creates with intervals of 0.1 between 0 and 1.

Then we put the data items into the bins with

digitized = numpy.digitize(data, bins)

And we get the means of the values in each bin with

[data[digitized == i].mean() for i in range(1, len(bins))]

Conclusion

To bin data in Python with scipy or numpy, we can use the linspace method to create the bins.

And then we call digitize to put the data into the bins`.