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  2. List of free geology software - Wikipedia

    en.wikipedia.org/wiki/List_of_free_geology_software

    This is a list of free and open-source software for geological data handling and interpretation. The list is split into broad categories, depending on the intended use of the software and its scope of functionality. Notice that 'free and open-source' requires that the source code is available and users are given a free software license.

  3. Matplotlib - Wikipedia

    en.wikipedia.org/wiki/Matplotlib

    Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.

  4. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    Orange, an open-source data mining and machine learning software suite. Python, an open-source programming language widely used in data mining and machine learning. R, an open-source programming language for statistical computing and graphics. Together with Python one of the most popular languages for data science.

  5. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    However, if data is a DataFrame, then data['a'] returns all values in the column(s) named a. To avoid this ambiguity, Pandas supports the syntax data.loc['a'] as an alternative way to filter using the index. Pandas also supports the syntax data.iloc[n], which always takes an integer n and returns the nth value, counting from 0. This allows a ...

  6. MATLAB - Wikipedia

    en.wikipedia.org/wiki/MATLAB

    MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages. Although MATLAB is intended primarily for numeric computing, an optional toolbox uses the MuPAD symbolic engine allowing access to symbolic computing abilities.

  7. Data wrangling - Wikipedia

    en.wikipedia.org/wiki/Data_wrangling

    Data wrangling can benefit data mining by removing data that does not benefit the overall set, or is not formatted properly, which will yield better results for the overall data mining process. An example of data mining that is closely related to data wrangling is ignoring data from a set that is not connected to the goal: say there is a data ...

  8. Multidimensional scaling - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_scaling

    It is also known as Principal Coordinates Analysis (PCoA), Torgerson Scaling or Torgerson–Gower scaling. It takes an input matrix giving dissimilarities between pairs of items and outputs a coordinate matrix whose configuration minimizes a loss function called strain, [2] which is given by (,,...,) = (, (),) /, where denote vectors in N-dimensional space, denotes the scalar product between ...

  9. DBSCAN - Wikipedia

    en.wikipedia.org/wiki/DBSCAN

    As a rule of thumb, minPts = 2·dim can be used, [9] but it may be necessary to choose larger values for very large data, for noisy data or for data that contains many duplicates. [ 4 ] ε: The value for ε can then be chosen by using a k-distance graph , plotting the distance to the k = minPts -1 nearest neighbor ordered from the largest to ...