Week 3-4: Learning Data Frame
For the past few weeks, I have learning the basics of Python and though I still have room for improvement, I now have the necessary skills to apply my newly obtained knowledge to learn Data Frame. Long story short, Data Frame is a Data Structure used to represent data with rows and columns (tabular or excel spreadsheet-like data). This is really useful for organizing large amounts of data and unorganized data sets.
The data that I will be using is from Kaggle with this link:
This CSV Parser provides public company data on over 7000 customers, which is more than enough data needed to make a strong inference on Market Churning. The data on the customers include: gender, age, access to tech support, type of contract, payment method, monthly/total charges, etc. I will be importing this exact data set into my code in Python.
Data Frame will be extremely useful in my scenario as it is extremely good with data organization and sorting, which will be extremely crucial to my project in the later stages of statistical analysis and creating the predictive model itself. I will be running Python using Jupyter Notebook as I find this platform to be the most convenient.
For the next few weeks of my senior project, I will be learning more about Data Frame and how to specifically apply it to my own project. This will include learning more about the possible operations and methods used in Data Frame and how it can be used to progress my project.
- “Building Java Programs – A Back To Basics Approach” 4th Edition, Stuart Reges & Marty Stepp