Intro to Data Analysis Workflows in Python with Pandas
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Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data. Data cleansing may be performed interactively with data wrangling tools, or as batch processing through scripting.
Data Collection is most likely to appear on Data Analyst job descriptions where we found it mentioned 11.9 percent of the time.