Utilize SQL to conduct a comprehensive analysis of pizza sales data, aiming to uncover patterns, trends, and insights that will inform strategic decision-making and enhance overall business efficiency.

Fast groupby-apply operations in python.

Perform Clustering for the crime data and identify the number of clusters formed and draw inferences. Data Description: Murder -- Muder rates in different places of United States Assualt- Assualt rate in different places of United States UrbanPop - urban population in different places of United States Rape - Rape rate in different places of Unit…

Unsupervised-ML---Hierarchical-Clustering-University Data. Import libraries, Import dataset, Create Normalized data frame (considering only the numerical part of data), Create dendrograms, Create Clusters, Plot Clusters.

Pandas groupby method used to extract data from tips dataset

Project to analyze key information from Culinary Jorney, a marketplace Company, and develop an initial strategy to lead the entire team effectively.

This Project aims at analysing 12 months’ worth of sales data containing hundreds of thousands of electronics store purchases broken down by month, product type, cost, purchase address, etc.

Assignment-07-DBSCAN-Clustering-Crimes. Perform Clustering for the crime data and identify the number of clusters formed and draw inferences.

Understanding Pandas, Groupby Function, Filtering Function

Learning "Pandas" Library

Using Python and Jupyter Notebook, school district's data is cleared of inaccuracies.

Prediction of house price using Linear Regression Supervised Machine learning Algorithm

A lecture on introductory data wrangling for my 3rd year Physics and Space Sciene students.

Perform DataFrame operations in Pandas for a more in-depth look at data wrangling in practice

DS Foundations II | A/B Testing for ShoeFly.com

Created summary DataFrame of ride-sharing data by city type using Python and multiple-line graph of weekly fares by city type using Pandas and Matplotlib.

Used libraries and functions as follows:

Created a summary DataFrame of the ride-sharing data by city type of a Uber-like company (Pyber). Then, using Pandas and Matplotlib, I created a multiple-line graph that shows the total weekly fares for each city type. Finally, I made a written report that summarizes how the data differs by city type and how those differences can be used by deci…

A better way to summerize a table information in pandas

Pair Programming – NumPy & Pandas Project – collaboratively applied NumPy and Pandas for EDA, data cleaning, null handling, and transformations, including groupby/apply operations on real datasets.