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  2. pandas (software) - Wikipedia

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

    If data is a Series, then data['a'] returns all values with the index value of a. 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.

  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. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data."

  5. File comparison - Wikipedia

    en.wikipedia.org/wiki/File_comparison

    Displaying the differences between two or more sets of data, file comparison tools can make computing simpler, and more efficient by focusing on new data and ignoring what did not change. Generically known as a diff [ 1 ] after the Unix diff utility , there are a range of ways to compare data sources and display the results.

  6. Data differencing - Wikipedia

    en.wikipedia.org/wiki/Data_differencing

    Main concerns for data differencing are usability and space efficiency (patch size).. If one simply wishes to reconstruct the target given the source and patch, one may simply include the entire target in the patch and "apply" the patch by discarding the source and outputting the target that has been included in the patch; similarly, if the source and target have the same size one may create a ...

  7. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

  8. Wide and narrow data - Wikipedia

    en.wikipedia.org/wiki/Wide_and_narrow_data

    Many statistical and data processing systems have functions to convert between these two presentations, for instance the R programming language has several packages such as the tidyr package. 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 ...

  9. Bivariate analysis - Wikipedia

    en.wikipedia.org/wiki/Bivariate_analysis

    Like univariate analysis, bivariate analysis can be descriptive or inferential. It is the analysis of the relationship between the two variables. [ 1 ] Bivariate analysis is a simple (two variable) special case of multivariate analysis (where multiple relations between multiple variables are examined simultaneously).