DataScience Classroomnotes 04/Jul/2022

ufunc

Creating own ufunc

  • To create own ufunc, we need to define a function just like normal functions in python and add it to the Numpy ufunc library from the frompyfunc() method
  • This frompyfunc() method takes the following arguments
    • function – name of the function
    • the numper of input argument (array)
    • the number of output arrays
      Preview
  • Arthimetic ufuncs
    Preview
  • Decimal rounding ufuncs: There are five ways of rounding off decimals in numpy
    • truncation
    • flx
    • rounding
    • floor
    • cell
      Preview
  • Logarithms
    Preview
  • LCM (Lowest common multiple) and GCD (Greatest common Denominator)/HCF
    Preview
  • Trignometric functions
    Preview
  • Sets
    Preview
  • Refer Here for the jupyter notebook

Pandas

  • The primary data structures of the pandas are
    • one dimensional => Series
    • two dimesnional => DataFrame
  • Pandas is a python package (library) for data analysis
  • Pandas is a toolbox for data manipulation operations
    • sorting
    • filtering
    • cleaning
    • deduping
    • aggregating
    • pivoting
    • many more
  • Pandas is an opensource library Refer Here
  • Pandas work seamlessly with numbers, text, dates, time, missing data and more.
    Preview
  • Refer Here for the jupyter notebook.

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