R for Reproducible Scientific Analysis
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Updated
Jun 11, 2024 - R
R for Reproducible Scientific Analysis
OpenRefine is a free, open source power tool for working with messy data and improving it
Prepping tables for machine learning
Zui is a powerful desktop application for exploring and working with data. The official front-end to the Zed lake.
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
CSVs sliced, diced & analyzed.
This repository is created as part of the Data Science Coursework Birzeit university
An trend analysis of the ground temperature of world cities
Is the Temperature of World Cities Increasing? A trend analysis using tableau.
Select, put and delete data from JSON, TOML, YAML, XML and CSV files with a single tool. Supports conversion between formats and can be used as a Go package.
Predicting Rocket Launch Success
Using Data Wrangling Techniques to Identify which types of unclaimed properties are more important for financial institutions to focus on -- Data Wrangling Project focused on Data Cleaning, Extraction, Transformation and Reporting
The data comes from the FBI's National Instant Criminal Background Check System. The NICS is used by to determine whether a prospective buyer is eligible to buy firearms or explosives.
Multithreaded package for working with tabular data in Julia
Materi praktik analisis data dengan SQL.
Basics of manipulating, pre-processing, cleaning, and wrangling data in Python
This repository contains the project materials for optimising e-commerce conversion rates through comprehensive data analysis. Leveraging SQL, MySQL, Power BI, and other tools, explore key factors influencing website performance. From data collection to actionable insights and recommendations,
Data-driven project aiding University of Leicester students in finding affordable housing through Python scraping, Excel analysis, and PowerPoint visualisation. Insights on rental prices, property types, and optimal locations.
In this project, we predict whether the Falcon 9 first stage will land successfully by following the data science methodology.
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