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Free and open-source software portal; Pyspread is a non-traditional spreadsheet.Cells in pyspread's grid accept expressions in the Python programming language. [2] A cell can return any Python object, which allows calculations with vectors, matrices, fractions, arbitrary precision numbers and symbols.
When the model is run, the system automatically reads input data from the spreadsheet and provides it to the model, and then writes the model results back to the spreadsheet. SolverStudio works with a range of commercial and open source modelling systems. By default, it uses PuLP, an open-source Python COIN-OR modelling language.
Sheets’ native file format has been OpenDocument since version two and previously used its own XML format, compressed with ZIP. Sheets also has the ability to import several spreadsheet formats, including XLS ( Microsoft Excel ), Applix Spreadsheet , Quattro Pro , CSV , dBase, Gnumeric , SXC ( OpenOffice.org XML ), Kexi and TXT.
Kingsoft Office Spreadsheets 2012 – For MS Windows. Both free and paid versions are available. It can handle Microsoft Excel .xls and .xlsx files, and also produce other file formats such as .et, .txt, .csv, .pdf, and .dbf. It supports multiple tabs, VBA macro and PDF converting. [10] Lotus SmartSuite Lotus 123 – for MS Windows. In its MS ...
[citation needed] It takes its name from the poem Beautiful Soup from Alice's Adventures in Wonderland [5] and is a reference to the term "tag soup" meaning poorly-structured HTML code. [6] Richardson continues to contribute to the project, [ 7 ] which is additionally supported by paid open-source maintainers from the company Tidelift.
SeaTable is a no-code platform [2] that allows users to develop and implement business processes. [3] The cloud collaboration service SeaTable is developed by the GmbH of the same name with headquarters in Mainz and additional offices in Berlin and Beijing.
OpenRefine is an open-source desktop application for data cleanup and transformation to other formats, an activity commonly known as data wrangling. [3] It is similar to spreadsheet applications, and can handle spreadsheet file formats such as CSV, but it behaves more like a database.
Pandas is built around data structures called Series and DataFrames. Data for these collections can be imported from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. [8] A Series is a 1-dimensional data structure built on top of NumPy's array.