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  2. 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 ...

  3. 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.

  4. Help:Advanced table formatting - Wikipedia

    en.wikipedia.org/wiki/Help:Advanced_table_formatting

    Instead of trying to make a super-cell that spans rows/columns, split it into smaller cells while leaving some cells intentionally empty. Use a non-breaking space with   or {} in empty cells to maintain the table structure. Custom CSS styling: Override the wikitable class defaults by explicitly specifying: border-collapse: collapse;

  5. Help:Table - Wikipedia

    en.wikipedia.org/wiki/Help:Table

    A table is an arrangement of columns and rows that organizes and positions data or images. Tables can be created on Wikipedia pages using special wikitext syntax, or HTML syntax, and many different styles and tricks can be used to customise them.

  6. Tab-separated values - Wikipedia

    en.wikipedia.org/wiki/Tab-separated_values

    Tab-separated values (TSV) is a simple, text-based file format for storing tabular data. [3] Records are separated by newlines , and values within a record are separated by tab characters . The TSV format is thus a delimiter-separated values format, similar to comma-separated values .

  7. Data cleansing - Wikipedia

    en.wikipedia.org/wiki/Data_cleansing

    Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database. It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [ 1 ]

  8. Isolation forest - Wikipedia

    en.wikipedia.org/wiki/Isolation_forest

    Isolation Forest is an algorithm for data anomaly detection using binary trees.It was developed by Fei Tony Liu in 2008. [1] It has a linear time complexity and a low memory use, which works well for high-volume data.

  9. Apache Parquet - Wikipedia

    en.wikipedia.org/wiki/Apache_Parquet

    Apache Parquet is a free and open-source column-oriented data storage format in the Apache Hadoop ecosystem. It is similar to RCFile and ORC, the other columnar-storage file formats in Hadoop, and is compatible with most of the data processing frameworks around Hadoop.