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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.
Pandas is built around data structures called Series and DataFrames. Data for these collections can be imported from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. [8] A Series is a 1-dimensional data structure built on top of NumPy's array.
A generic list box. A list box is a graphical control element that allows the user to select one or more items from a list contained within a static, multiple line text box. The user clicks inside the box on an item to select it, sometimes in combination with the ⇧ Shift or Ctrl in order to make multiple selections. "Control-clicking" an item ...
Each row must have the same number of cells as the other rows, so that the number of columns in the table remains consistent. With colspan and rowspan cells can span several columns or rows; (see § Mélange, below)
A column selection is a text selection feature found in text editors which allows the user to select characters in a grid-like fashion, selecting characters in several lines at the same columns. This is usually initiated by pressing the alt key (instead of the shift key, which creates a continuous selection) to select text when dragging .
Standard examples of data-driven languages are the text-processing languages sed and AWK, [1] and the document transformation language XSLT, where the data is a sequence of lines in an input stream – these are thus also known as line-oriented languages – and pattern matching is primarily done via regular expressions or line numbers.
The two most common representations are column-oriented (columnar format) and row-oriented (row format). [ 1 ] [ 2 ] The choice of data orientation is a trade-off and an architectural decision in databases , query engines, and numerical simulations. [ 1 ]
The following example of a SELECT query returns a list of expensive books. The query retrieves all rows from the Book table in which the price column contains a value greater than 100.00. The result is sorted in ascending order by title. The asterisk (*) in the select list indicates that all columns of the Book table should be included in the ...