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  2. pandas (software) - Wikipedia

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

    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 .

  3. Dataframe - Wikipedia

    en.wikipedia.org/wiki/Dataframe

    Dataframe may refer to: A tabular data structure common to many data processing libraries: pandas (software) § DataFrames; The Dataframe API in Apache Spark; Data frames in the R programming language; Frame (networking)

  4. Matrix addition - Wikipedia

    en.wikipedia.org/wiki/Matrix_addition

    In mathematics, matrix addition is the operation of adding two matrices by adding the corresponding entries together. For a vector , v → {\displaystyle {\vec {v}}\!} , adding two matrices would have the geometric effect of applying each matrix transformation separately onto v → {\displaystyle {\vec {v}}\!} , then adding the transformed vectors.

  5. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    5,000 unique microstructures, all samples have been acquired 3 times with two different cameras. Original PNG files, sorted per camera and then per acquisition. MATLAB datafiles with one 16384 times 5000 matrix per camera per acquisition. 30,000 Images and .mat files Authentication 2012 [183] S. Voloshynovskiy, et al. PharmaPack Dataset

  6. Pivot table - Wikipedia

    en.wikipedia.org/wiki/Pivot_table

    Python data analysis toolkit pandas has the function pivot_table [16] and the xs method useful to obtain sections of pivot tables. [ citation needed ] R has the Tidyverse metapackage, which contains a collection of tools providing pivot table functionality, [ 17 ] [ 18 ] as well as the pivottabler package.

  7. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    In particular, he held that confusing the two types of analyses and employing them on the same set of data can lead to systematic bias owing to the issues inherent in testing hypotheses suggested by the data. The objectives of EDA are to: Enable unexpected discoveries in the data; Suggest hypotheses about the causes of observed phenomena

  8. Spearman's rank correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Spearman's_rank_correlation...

    Python has many different implementations of the spearman correlation statistic: it can be computed with the spearmanr function of the scipy.stats module, as well as with the DataFrame.corr(method='spearman') method from the pandas library, and the corr(x, y, method='spearman') function from the statistical package pingouin.

  9. AoS and SoA - Wikipedia

    en.wikipedia.org/wiki/AOS_and_SOA

    "Data frames," as implemented in R, Python's Pandas package, and Julia's DataFrames.jl package, are interfaces to access SoA like AoS. The Julia package StructArrays.jl allows for accessing SoA as AoS to combine the performance of SoA with the intuitiveness of AoS. Code generators for the C language, including Datadraw and the X Macro technique.