Predicting price and customer satisfaction: Airbnb data
My collection of visualizing different datasets using (Matplotlib, Seaborn, and Folium) packages for Python
Determines the price of the launch. Also, determines if SpaceX will reuse the first stage.
Acest repo conține materiale, seturi de date și soluții care au fost folosite în cadrul Școlii de vară Astra, prima ediție, 2021
Visualising World Mortality Rates
• Applied data wrangling and data visualisation skills on stroke dataset and created visualisations using the R programming language in Rstudio. • Prepared a report using Latex which included a set of decision supports using visualisations • Created a web-based application with interactive graphs (using shiny package from R) to tell a direct story.
Explore Diwali Sales Data Analysis: a project dissecting 11,251 records with 15 columns to uncover customer demographics and buying trends during the festive season. The objective? Understand customer behavior, identify key demographics and product categories driving sales. Utilizing Python libraries like Pandas, NumPy, Matplotlib, and Seaborn, thi
Extensively worked on data cleaning and data wrangling to analyze the number of deaths between years 2000-2023 with the help of pie charts, bar charts, word cloud and heat maps. Used time series analysis to check if the events of death follow stationarity and forecasted the trends.
This folder contains work I submitted as part of the technical interview for a data science position at CEMA
This repository is demonstration of Pandas library of Python's super powers.
Why data analysis? , How to understand the problem, what to do for data analysis, and how clean the data for building Machine Learning models
Oftentimes, we come across data that isn't in the form that we need to make joins, when that happens, we can convert those using simple python scripts I use the gene ontology OBO format and convert it into tabular format for making joins with other tables using this python script.
This repository contains the projects I worked on, in the course of completing my Udacity-Data Analyst Nanodegree course.
Performed data visualization using Tableau to analyze my own chess games played on lichess.org. I downloaded data from Lichess, and convert it from PGN format to CSV. Utilized various chartsto communicate insights, user-friendly interface.
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