Data can be found everywhere, in all shapes and forms. We can get it from the web, IoT sensors, emails, FTP, and databases. We can also collect it ourselves in a lab experiment, election polls, marketing polls, and social surveys. As a data professional, you should know how to handle a variety of datasets as that is a very important skill. We will discuss retrieving, processing, and storing various types of data in this chapter. This chapter offers an overview of how to acquire data in various formats, such as CSV, Excel, JSON, HDF5, Parquet, and pickle.
Sometimes, we need to store or save the data before or after the data analysis. We will also learn how to access data from relational and NoSQL (Not Only SQL) databases such as sqlite3, MySQL, MongoDB, Cassandra, and Redis. In the world of the21st-century web, NoSQL databases are undergoing...
