![]() append (entry_num ) entry_num += 1 just_the_occur. Word_frequency = 0 entry_num = 1 for entry in sorted_doc : if (entry = word ) : word_rank = entryNum word_frequency = entry just_the_rank. This essentially declares plt as a global variable that will be used throughout our script. In this program, we will import matplotlib and the class that we need (which is pyplot), passing it the plt alias. ![]() Using a text editor of your choice, create a new Python file and call it word_freq.py. Now that we have matplotlib installed on our computer, we can begin to create our project. To get the most out of this guide, you should be familiar with Python 3 and about the dictionary data type in particular.įinally, make sure you follow Step 1 - importing matplotlib of our How to Plot Data in Python 3 Using matplotlib as it is essential to have matplotlib installed for this project. You should have Python 3 and a programming environment already installed on your local computer or server. To be able to use this tutorial, make sure you have the following prerequisites: We will then graph the data we found using matplotlib. The program we will be creating will search through a plain text document and organize each unique word with its frequency. ![]() In this tutorial, we will be exploring graphing word frequency in a text corpus. When we analyze and visualize textual data we can bring to light general trends that can change the way we interpret the text. Textual data exists in many different forms, from journalism to social media to emails.
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