Data analysis and processing

There are a number of useful libraries for working with data, and you will want to use different libraries and techniques at different points of the data life cycle. For instance, in working with data, it is often useful to start with Exploratory Data Analysis (EDA). Later on, you will want to do cleanup, wrangling, various transformations for preprocessing, and so on. Here are some of the available Python libraries and their uses.

pandas

pandas is easily one of the most important libraries to use when doing anything with data in Python. Put simply, if you work with data in Python, you should know about pandas, and you should probably be using it. You can use it for several different things when working with data, such as the following:

• Reading data from an assortment of file types or from the internet
• EDA
• Extract, Transform, Load (ETL)
• Simple and quick data visualizations
• And much, much, more

If there is one Python...