# Histograms and Probability Density Function

In this lesson, we will learn about representing data using histograms and probability density functions.

## We'll cover the following

# Representing data #

One of the most common ways to represent a data set is to draw a histogram. For a histogram, you count how many data points fall within a certain interval. For example, how many data points are between 5 and 6. These intervals are called bins. The bar graph of the number of data points in each bin is called a histogram. The function to compute and plot a histogram is called `hist()`

and is part of the `matplotlib`

package. The simplest way of plotting a histogram is to let `hist()`

decide what bins to use; the default number of bins is `nbin=10`

.

`hist()`

even figures out where to put the limits of the bins. The `hist()`

function creates a histogram graph and *returns* a tuple of three items:

- The first item is an array of length
`nbin`

with the number of data points in each bin. - The second item is an array of length
`nbin+1`

with the limits of the bins. - The third item is a list of objects that represent the bars of the histogram; this is the least used item.

Let’s draw a histogram:

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