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Why is Python used in DS for data cleaning? | Intellipaat


Data Scientists must clean and transform massive data sets into usable formats. For better results, deal with redundant data by removing nonsensical outliers, malformed records, missing values, inconsistent formatting, and so on.

Obtaining a Data Science Course is vital for upskilling and staying current in the workplace.

Python libraries for data cleaning and analysis include Matplotlib, Pandas, Numpy, Keras, and SciPy. These libraries are used to load and clean data as well as perform effective analysis. For example, a CSV file named "Student" contains information about an institute's students such as their names, standard, address, phone number, grades, marks, and so on.

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