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  2. 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 ...

  3. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]

  4. Dask (software) - Wikipedia

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

    A Dask DataFrame comprises many smaller Pandas DataFrames partitioned along the index. It maintains the familiar Pandas API, making it easy for Pandas users to scale up DataFrame workloads. During a DataFrame operation, Dask creates a task graph and triggers operations on the constituent DataFrames in a manner that reduces memory footprint and ...

  5. Quartile - Wikipedia

    en.wikipedia.org/wiki/Quartile

    Quartile Method Microsoft Excel QUARTILE.EXC Method 4 Microsoft Excel QUARTILE.INC Method 3 TI-8X series calculators 1-Var Stats Method 1 R fivenum Method 2 Python numpy.percentile Method 3 Python pandas.DataFrame.describe Method 3

  6. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters).

  7. Grouped data - Wikipedia

    en.wikipedia.org/wiki/Grouped_data

    Another method of grouping the data is to use some qualitative characteristics instead of numerical intervals. For example, suppose in the above example, there are three types of students: 1) Below normal, if the response time is 5 to 14 seconds, 2) normal if it is between 15 and 24 seconds, and 3) above normal if it is 25 seconds or more, then the grouped data looks like:

  8. Wide and narrow data - Wikipedia

    en.wikipedia.org/wiki/Wide_and_narrow_data

    The pandas package in Python implements this operation as "melt" function which converts a wide table to a narrow one. The process of converting a narrow table to wide table is generally referred to as "pivoting" in the context of data transformations.

  9. Skip list - Wikipedia

    en.wikipedia.org/wiki/Skip_list

    () operations, which force us to visit every node in ascending order (such as printing the entire list), provide the opportunity to perform a behind-the-scenes derandomization of the level structure of the skip-list in an optimal way, bringing the skip list to (⁡) search time. (Choose the level of the i'th finite node to be 1 plus the number ...