This repository contains python-based data analysis examples that I did for fun.
This includes Python and pandas examples to play around with data files and apply different operations, for e.g.,
-
data cleaning and data munging ==>handling missing or null values (using different data imputation techniques - majority, median, using percentiles), adding new fields based on existing fields, combining fields, extracting data from existing fields,
-
data analysis - exploring the pattern of data using different numerical and graphical techniques (creating distribution charts, analyzing the percentiles)
-
data visualization - exploring matplotlib, seaborn, and pandas in-build visualization technique to visualize the pattern of data, analyze the correlation between the available features and target variable
-
predictive models - exploring different Machine Learning algorithms (Decision Tree, SVM, Logistic Regression, K-Nearest neighbor, etc) for different prediction problems.
The list will keep on growing! Stay tuned!