Explore and practice the different types of plots that are instrumental in visualizing your data.

Python Data Analysis and Visualization

Visualization using Matplotlib for Python

The histogra is an important graph in statistics and data analysis. It can be used to help people quickly understand the distribution of data. In order to draw a histogram, we follow the steps outlined below:

- Step 1: #concept=Bin#Bin#concept# the range of your data.
- Step 2: Divide the entire range of values into their corresponding bins.
- Step 3: Count how many values fall into each different bin


# What is `hist()`?

The function in Matplotlib that we can use to draw a histogram is `hist()`. Below are some of the important parameters that we may need:

- `x`: Our input values, either a single list/array or multiple sequences of arrays.
- `bins`: If `bins` is set with an integer, it will define the number of equal-width bins within a range. If `bins` is set with a sequence, it will define the bin edges, including the left edge of the first bin and the right edge of the last bin.
- `histtype`: Sets the style of the histogram. The default value is `bar`. `step` generates a line plot that is unfilled by default. `stepfilled` generates a line plot that is filled by default.
- `density`: Sets True or False. The default is set to False. If True, the histogram will be normalized to form a probability density.
- `cumulative`: Sets True or -1. If True, then a histogram is computed where each bin gives the count in that bin plus all bins for smaller values. 


In this lesson, we will learn how to represent the distribution of numerical data using a histogram.

How to Draw a Histogram Plot