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Origin Workbook with sparklines above data columns, this allows a quick glance of the data without plotting them. Origin is primarily a GUI software with a spreadsheet front end. Unlike popular spreadsheets like Excel, Origin's worksheet is column oriented. Each column has associated attributes like name, units and other user definable labels.
Wes McKinney is an American software developer and businessman. He is the creator and "Benevolent Dictator for Life" (BDFL) of the open-source pandas package for data analysis in the Python programming language, and has also authored three versions of the reference book Python for Data Analysis.
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.
Download as PDF; Printable version; In other projects ... data analysis, ... came out in June 2010 and shares the same worksheet file structure as Mathcad 14.0. The ...
NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
DADiSP is designed to perform technical data analysis in a spreadsheet like environment. However, unlike a typical business spreadsheet that operates on a table of cells each of which contain single scalar values, a DADiSP Worksheet consists of multiple interrelated windows where each window contains an entire series or multi-column matrix.
Orange – A visual programming tool featuring interactive data visualization and methods for statistical data analysis, data mining, and machine learning. Pandas – Python library for data analysis. PAW – FORTRAN/C data analysis framework developed at CERN. R – A programming language and software environment for statistical computing and ...
In summary, data analysis and data science are distinct yet interconnected disciplines within the broader field of data management and analysis. Data analysis focuses on extracting insights and drawing conclusions from structured data, while data science involves a more comprehensive approach that combines statistical analysis, computational ...