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Pipeline Pilot is a software tool designed for data manipulation and analysis. It provides a graphical user interface for users to construct workflows that integrate and process data from multiple sources, including CSV files, text files, and databases. The software is commonly used in extract, transform, and load (ETL) tasks.
30+ files (v0.9) CSV Anomaly detection: 2020 (continually updated) [329] [330] Iurii D. Katser and Vyacheslav O. Kozitsin On the Evaluation of Unsupervised Outlier Detection: Measures, Datasets, and an Empirical Study Most data files are adapted from UCI Machine Learning Repository data, some are collected from the literature.
It is free software released under the three-clause BSD license. [2] The name is derived from the term "panel data", an econometrics term for data sets that include observations over multiple time periods for the same individuals, [3] as well as a play on the phrase "Python data analysis".
[13] [14] All CS50x course materials are free and there is no fee to complete the course, though various verified certificates are available for a fee. [15] As of 2024, CS50x teaches the languages C, Python, SQL, HTML, CSS, and JavaScript. It also teaches fundamental computer science concepts including data structures and the Flask framework. [13]
A common use case for ETL tools include converting CSV files to formats readable by relational databases. A typical translation of millions of records is facilitated by ETL tools that enable users to input csv-like data feeds/files and import them into a database with as little code as possible.
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
JMP software is partly focused on exploratory data analysis and visualization. It is designed for users to investigate data to learn something unexpected, as opposed to confirming a hypothesis. [ 5 ] [ 26 ] [ 43 ] JMP links statistical data to graphics representing them, so users can drill down or up to explore the data and various visual ...