Discussion 1: Pandas NoSQL Dataframes
A number of big data NoSQL schemes use dataframes. Dataframes are essentially two-dimensional document stores in which columns hold variable data types. A particular type of dataframe is offered by the Pandas Python package.
This Discussion focuses on the methods used by Pandas NoSQL dataframes for big data storage and manipulation.
To prepare:
• Review the resources and media (attached as source to order) for this week.
• Research online sources, including articles relating to Pandas and other dataframe types.
Use this for each paragraph:
Post a 350- to 500-word response in APA7 format in which you include:
• Explain the methods used by Pandas NoSQL dataframes to store and manipulate big data.
• Explain how big data NoSQL databases, such as Pandas dataframes, facilitate creation (insertion), retrieval (queries), update (edits), and deletion (removal) operations on stored data (collectively abbreviated CRUD storage primitives).
Sources to be used for citation and reference:
Laureate Education (Producer). (2017e). Document-oriented NoSQL storage systems [Video]. Walden University Blackboard. https://class.waldenu.edu
Laureate Education (Producer). (2017d). Data-frame-based document-oriented storage models [Video]. Walden University Blackboard. https://class.waldenu.edu
Achari, S. (2015g). Storage component – Hbase. In Hadoop essentials (Community experience distilled). Packt Publishing.
Note: Chapter 5