Define a procedure histogram() that takes a list of integers and prints a histogram to the screen| Histogram procedure| printing histogram| Python histogram function| Python programming

 How to Visualize Data with Python: Defining a Procedure Histogram()

When it comes to analyzing data, visualization is key. Being able to see the patterns and trends in your data can make all the difference in understanding it. Luckily, Python has a built-in function for creating histograms, which is a powerful tool for visualizing data. In this blog post, we'll define a procedure called histogram() that takes a list of integers and prints a histogram to the screen.

Before we get into the nitty-gritty of the code, let's briefly discuss what a histogram is and why it's useful. A histogram is a graphical representation of a frequency distribution, which is essentially a way to show how often certain values occur in a dataset. It's a great way to get a quick sense of the shape of your data, including its range, distribution, and outliers.

Now, let's dive into the code. Here's how you can define a procedure histogram() in Python:

def histogram(int_list):

    for i in int_list:

        print('*' * i)

The procedure takes a single argument, int_list, which should be a list of integers. The for loop iterates over each integer in the list, and the print statement uses string multiplication to print a string of asterisks of length i. The result is a histogram where the height of each bar corresponds to the frequency of the corresponding value in the list.

To use the histogram() procedure, simply pass it a list of integers as an argument. For example:

data = [1, 3, 2, 4, 3, 5, 2, 3, 1, 4]

histogram(data)

This will output the following histogram to the screen:

*

***

**

****

***

*****

**

***

*

****

As you can see, the histogram accurately represents the frequency distribution of the data. The tallest bar corresponds to the value 3, which occurs three times in the list, while the shortest bar corresponds to the value 5, which only occurs once.

In conclusion, defining a procedure like histogram() is a great way to quickly and easily visualize data in Python. By representing the frequency distribution of your data as a histogram, you can gain valuable insights and make informed decisions. So go ahead and try it out for yourself – you might be surprised at what you discover!

Code - 

def histogram(l1):

    for i in l1:

            print('*'*i)