Python Libraries-Applications
Python Libraries-Applications NumPy Python approaches data analysis by array - oriented computing which becomes the basis for all data processing tasks. With NumPy, it is possible to implement multidimensional arrays and apply techniques ranging from simple cleaning and merging to advanced tasks such as linear algebra and statistical analysis. Once installed, NumPy provides the foundation for other libraries such as pandas, scikit-learn, and SciPy. The functionality that is provided in NumPy applies to many data processing tasks. Pandas The pandas library in Python is used for doing data manipulation. Origin of the library name comes from Panel Data and Statistics. pandas provides efficient ways to: Format data into dataframes which makes it easy to identify and delete specific records, columns or chunks of data using indexing All file types such as csv, json, xml, excel can be called and converted to dataframes with a simple function. pandas uses loc and iloc functions to ...