Data visualization - qualitative & quantitative data (Airbnb listings for NY)
PyVizNotebook is a collection of Matplotlib visualizations demonstrating a wide range of plot types and techniques for data visualization. Whether you're a beginner looking to learn or an experienced developer seeking inspiration, this repository offers a diverse set of examples to explore.
Popularity of engine fuel types (1982 - 2016)
This repository consists of notebooks where I learned the basics of getting started with data analysis using Python libraries
911 Calls Capstone Project - Analysing the frequency of emergency 911 calls. This project is developed on a Jupyter notebook using Python with Numpy, Pandas data analysis libraries along with Matplotlib and seaborn data visualization libraries.
Career Foundry data analytics project to provide a client recommendations on a marketing strategy. Jupyter notebooks include cleaning and merging data along with creating new columns to offer the best understanding of consumers' interactions with products.
Embarking on a vital linguistic preservation initiative, our project surveyed the diminishing popularity of rural languages across 20 states of India. Leveraging the power of Computer Science, we meticulously analyzed and visualized the data using Heatmap with Seaborn (sns) in Jupyter Notebook.
Using Python libraries in a Jupyter Notebook, this project explores Diwali sales data, revealing valuable insights: Buyer Dynamics: Females drive sales, showcasing higher purchasing power than males. Age Impact: The 26-35 age group, primarily females, contributes significantly.Marital Influence: Married women exhibit strong purchasing potential.
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