Processing Data with Python

Processing data is used in virtually every field these days. It is used for analyzing web traffic to determine personal preferences, gathering scientific data for biological analysis, analyzing weather patterns, business practices, and on. Data can take on many different forms and come from many different sources. Python is an open-source (free) programming language that is used in web programming, data science, artificial intelligence, and many scientific applications. It has libraries that can be used to parse and quickly analyze the data in whatever form it comes in, whether it be in XML, CSV, or JSON format. Data cleaning is an important aspect of processing data, particularly in the field of data science. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

• Processing Data with Python
• Processing data is used in virtually every field these days. It is used for analyzing web traffic to determine personal preferences, gathering scientific data for biological analysis, analyzing weather patterns, business practices, and on. Data can take on many different forms and come from many different sources. Python is an open-source (free) programming language that is used in web programming, data science, artificial intelligence, and many scientific applications. It has libraries that can be used to parse and quickly analyze the data in whatever form it comes in, whether it be in XML, CSV, or JSON format. Data cleaning is an important aspect of processing data, particularly in the field of data science. In this course, you will create an application that reads data in a couple of different formats using the Pandas library. You will perform statistical analysis on the data. You will also see how to clean specific areas from the data set to produce valid information.