iemeka / data-scraping--structure-and-storage Goto Github PK

Using clearly written python code:

• Colors were extracted from the html file python_class_test.html using regular expression

• The data extracted was stored in a dictionary using color name as key and their frequency as values.

• The dictionary was converted to a pandas object. Using pandas:

  • The mean color was determined
  • The mode color was determined
  • The median color was determined
  • Variance of the color was determined
  • If a color was chosen at random, the probability of selecting a red color was determined

• The colors and their frequencies were stored in a postgresql database using PostgreSQL database adapter for Python

• Finally a program to sum the first 50 fibonacci sequence

Checkout my predictive analytics on a dataset : https://iemeka.github.io/predictive-analytics--determination-of-insurance-premium-charge/