pandas

Reads in a csv file (uploaded to Amazon S3 bucket) as a pandas dataframe. Performs basic data transformations and adds a column with flags based on ranges in temperature values in the dataframe. Uploads a copy of the modified data as a csv file in a different bucket. Emails list of recipients with a presigned URL to download the object.

Jupyter notebook to pull data from the FPL website, specifically made for H2H Draft Leagues.

The main database of the French National Health Data System (SNDS) contains data from Health Insurance reimbursements, hospital treatment and medical causes of death. In order to characterise its use for health research and innovation, an interactive cartography has been produced to understand the framework of its use and to identify the stakeholders of the SNDS ecosystem. A bibliographic search via PubMed (available here), LiSSa, HAL was conducted to identify scientific articles published starting January 2007 on studies using SNDS data. The list of authors, their affiliations, keywords, the number of citations and much more were collected. A descriptive analysis was carried out in order to assess temporal and geographical trends in the use of SNDS main database. The graphs where generated with networkx, a python package used for the creation manipulation and study of complex networks. To generate the Author/Affiliations graphs we first create the adjacency matrix between the Authors/Affiliations and the article PMIDs. We then use the networkx.Graph class to create the needed undirected graphs, using the adjacency matrices as the data to intialize the graphs.

A dataframe library for Crystal.

This project focuses on extracting and visualizing stock data using Python libraries such as yfinance for historical stock prices and web scraping techniques to gather company revenue data. It provides a comprehensive analysis by plotting both stock prices and revenues over time for companies like Tesla and GameStop.

Project for E-commerce. Product analysis, cohort analysis, RFM analysis in Python.

Notebooks for Pandas, Spark and Python experiments.

Plática "Olvidate de Excel, bienvenido pandas" en Nerdearla México 2024 del 2024-11-07. https://nerdear.la/en/agenda/olvidate-de-excel-bienvenido-pandas/

This project repository offers a comprehensive collection of solutions to LeetCode problems that require the use of the Pandas library. These solutions demonstrate effective data manipulation, analysis, and cleaning techniques using Pandas, providing valuable insights for those learning or practicing Pandas skills. The repository is organized for easy reference and learning from the provided examples.

This project predicts house prices using machine learning models based on the King County House Sales dataset. It explores Simple Linear, Multiple Linear, Polynomial, and Ridge Regression models, comparing their performance in terms of accuracy. The best model identified is Polynomial Regression, achieving an R² score of 0.75.

Proyecto que implementa una API de creación y venta de productos construido en Python usando el framework FastAPI, Pandas Dataframe para la manipulación de datos y archivos con formato Json para la persistencia de la información.

Common statistics and functions to work with financial time series.

Script para coletar dados json de paises, realizar tratamento e salvar dados em um arquivo Excel.

Praktisi Mengajar 2024 Teknik Informatika Universitas Nusa Putra

"I have created a Streamlit dashboard that provides detailed information about a single spider's chain. This dashboard assists our engineering team in investigating chain details, featuring graphs, CSV files, and other pertinent information related to spiders. The dashboard also includes interactive elements for data exploration, real-time updates, and customizable filters to analyze specific aspects of the spider's performance and behavior. Additionally, it integrates with our existing data pipelines to ensure seamless data retrieval and presentation."

A project to develop a non-invasive, AI-powered system for detecting lung cancer associated with combustion particles and fine particulate matter (PM2.5).

В данном репозитории находятся два проекта, демонстрирующие работу c данными в Python и на SQL, а также использование специализированных библиотек для статистических расчетов и визуализации данных, в Jupiter Notebook.