Map and Data Library (University of Toronto)

Often, the first step when working with data is to clean or wrangle it. This can involve normalizing the data by format or unit of measurement, reshaping rows and columns, converting files to different file formats, etc. For large datasets, researchers turn to tools, such as OpenRefine or programming languages, such as R, to assist in this task.

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Often, the first step when working with data is to clean or wrangle it. This can involve normalizing the data by format or unit of measurement, reshaping rows and columns, converting files to different file formats, etc. For large datasets, researchers turn to tools, such as OpenRefine or programming languages, such as R, to assist in this task.

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