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  2. pandas (software) - Wikipedia

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

    [4]: 114 A DataFrame is a 2-dimensional data structure of rows and columns, similar to a spreadsheet, and analogous to a Python dictionary mapping column names (keys) to Series (values), with each Series sharing an index. [4]: 115 DataFrames can be concatenated together or "merged" on columns or indices in a manner similar to joins in SQL.

  3. Clamp (function) - Wikipedia

    en.wikipedia.org/wiki/Clamp_(function)

    Although spreadsheets like Excel, Open Office Calc, or Google Sheets don't provide a clamping function directly, the same effect can be achieved by using functions like MAX & MIN together, by MEDIAN, [8] [9] or with cell function macros. [10] When attempting to do a clamp where the input is an array, other methods must be used. [11]

  4. Comma-separated values - Wikipedia

    en.wikipedia.org/wiki/Comma-separated_values

    Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record.

  5. Data transformation (computing) - Wikipedia

    en.wikipedia.org/wiki/Data_transformation...

    Code generation is the process of generating executable code (e.g. SQL, Python, R, or other executable instructions) that will transform the data based on the desired and defined data mapping rules. [4] Typically, the data transformation technologies generate this code [5] based on the definitions or metadata defined by the developers.

  6. 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.

  7. Exponential smoothing - Wikipedia

    en.wikipedia.org/wiki/Exponential_smoothing

    Exponential smoothing or exponential moving average (EMA) is a rule of thumb technique for smoothing time series data using the exponential window function.Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time.

  8. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    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. TinkerPlots an EDA software for upper elementary and middle school students.

  9. Pivot table - Wikipedia

    en.wikipedia.org/wiki/Pivot_table

    Pivot tables are not created automatically. For example, in Microsoft Excel one must first select the entire data in the original table and then go to the Insert tab and select "Pivot Table" (or "Pivot Chart"). The user then has the option of either inserting the pivot table into an existing sheet or creating a new sheet to house the pivot table.