pandas

Follow a CSV file to the number it reports: switch on one fault at a time, predict what a hand-written loop and a library default each report, and hold a claim against the rows.

Flagship Data Analyst portfolio: 4 business audits (179K+ records) + contract agent + weekly revenue reconciliation engine | SQL, Python, Power BI, Excel, Streamlit

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.

• Developed and deployed an interactive media analytics dashboard analyzing 150 English-language political news articles across six major South Korean publications. • Applied TF-IDF vectorization and K-Means clustering to identify recurring themes and examine differences in political news coverage across publications. • Designed a Snowflake cloud analytics layer using relational tables and SQL reporting views to support publication-level comparisons, topic distributions, and NLP cluster analysis. • Integrated Snowflake with Streamlit using RSA key-pair authentication and role-based, read-only access, enabling secure retrieval of cloud-hosted analytics. • Deployed the application through GitLab and Render, delivering an accessible, interactive portfolio project with publication filters, visualizations, and downloadable analytical results.

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.

Projet SCAP permettant d'animer des ateliers autour de la data. Le but est de permettre aux auditrices et auditeurs de pratiquer dans la manipulation de données. Il y aura une partie SQL importante pour préparer une certification SQL (w3schools) et également une partie Python-Pandas pour la manipulation des données via un langage impératif et une librairie très populaire.

Python library to convert ros message streams to pandas dataframes.

Materials on various sections in Computer Science (CS). 🎓

Categorizza automaticamente i movimenti del conto BPER e genera un consuntivo mensile con grafici, budget, abbonamenti ricorrenti e suggerimenti di risparmio. Include uno userscript per esportare i movimenti dall'home banking.

Predicting 30-Day Hospital Readmission in Diabetic Patients

Python SDK for Special Relativity Financial Modeling: Lorentz factors, spacetime intervals and geodesic signals on OHLCV data with pandas.

Análisis de datos de principio a fin sobre 741.894 versiones de clases Java: calidad de datos (Pandas), modelo estrella y KPIs en SQL, dashboard en Power BI y evaluación de un modelo predictivo con validación por repositorio.

General purposes Jupyter Notebooks (XalapaCode presentations and data, testing, prototypes).

JSON-like data manipulation and transofrmation to and from nested parent-child and flat label-value data items.

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.

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

Data analysis with the pandas DataFrame library in Python.