Hello 🖐️!!!
This is a repository that works as a portfolio to showcase my programming abilities 💻.
In here you can find progect that involve Python
🐍 with data manipulation 💾. Some are only Python code, but there also some that use popular libraries like Pandas
🐼 and NumPy
📊 among others!!!
1.- NBA Trends Project:
Make insightful analysis and represent those results visually using libraries like scipy
, matplotlib
, and seaborn
into histograms 📊, scatterplots and boxplots.
2.- Airline Analysis:
Visualization for EDA
(Exploratoy Data Analysis). Messy dataset, exploring Univariate, Bivariate, and Multivariate Analysis. Using Pandas
🐼, NumPy
📊 and seaborn
📊 libraries to easily interpret data.
3.- Biodiversity Starter:
The goal of this project is to analyze biodiversity data from the National Parks Service, particularly around various species observed in different national park locations. This project will scope, analyze, prepare, plot data, and seek to explain the findings from the analysis using libraries like Pandas
🐼, scipy
, matplotlib
, seaborn
📊, and regex
.
3.- EDA: Diagnosing Diabetes:
Using EDA
(Exploratoy Data Analysis) to inspect clean and validate data from csv files. Using the famous the libraries Pandas
🐼 and NumPy
📊.
4.- Life Expectancy and GDP Starter:
Make insightful analysis and represent those results visually using libraries like scipy
, matplotlib
, and seaborn
into histograms 📊, scatterplots and boxplots.
5.- Page Funnel Visits:
Using Pandas
🐼 library, ETL
(Extract Transform, and Loading) the information from different csv filesto create useful DataFrames
. Then analyze the information to uncover patterns and obtain actionable insights.
6.- Cleaning US Census Data:
Using Pandas
and matplotlib
, diferent CSV
files were merged to perform data wrangling (munging) and tidying. Then being able to perfom data analysis on different populations with histograms 📊.
7.- U.S. Medical Insurance Costs: In this project, a CSV file with medical insurance costs will be investigated using Python basic fundamentals. The goal with this project will be to analyze various attributes within insurance.csv to learn more about the patient information in the file and gain insight into potential use cases for the dataset.
8.- Hurricane Analysis: Organize and manipulate data using Python lists and dictionaries to categorize the information from various hurricanes 🌪️.
9.- Product Defects:
Distribution theory usibg the Poisson distribution
to to rate the exoected parameter of defects.
10.- Reggie Linear Regression Skeleton:
Simple Linear Regresion
code with Python 🐍.
11.- Frida Kahlo Project: Using Python lists to regroup information.