Projects with this topic
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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.
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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.
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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.
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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.
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Common statistics and functions to work with financial time series.
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Script para coletar dados json de paises, realizar tratamento e salvar dados em um arquivo Excel.
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Praktisi Mengajar 2024 Teknik Informatika Universitas Nusa Putra
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"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."
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Script to read the Mathecamp timetable and derive certain files for the organization of the Mathecamp.
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A project to develop a non-invasive, AI-powered system for detecting lung cancer associated with combustion particles and fine particulate matter (PM2.5).
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Python library to convert ros message streams to pandas dataframes.
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FHIRPACK (FHIR Python Analysis Client and Kit) is a general purpose FHIR client and toolkit that simplifies the access, analysis and representation of FHIR and EHR data using PANDAS, an ETL philosophy and a functional syntax. FHIRPACK was designed and developed at IKIM MML (https://mml.ikim.nrw/) and HDDBS (https://dbs.ifi.uni-heidelberg.de/). Read more at https://zenodo.org/record/8006589
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njson: efficient JSON-like data transformation tool. Provide high-performance JSON-like data transformation to and from nested parent-child and flat label-value data items, such as Pandas Series with MultiIndex index.
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JSON-like data manipulation and transofrmation to and from nested parent-child and flat label-value data items.
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Allows user to open their bookmarked pages by using a search engine like interface.
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A Python module, primarily on linear and multiple regression including normalizing data, computing hypothesis, and evaluating cost.
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