## 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

- Arthimetic ufuncs

- Decimal rounding ufuncs: There are five ways of rounding off decimals in numpy
- truncation
- flx
- rounding
- floor
- cell

- Logarithms

- LCM (Lowest common multiple) and GCD (Greatest common Denominator)/HCF

- Trignometric functions

- Sets

- Refer Here for the jupyter notebook

## Pandas

- The primary data structures of the pandas are
- one dimensional =>
**Series** - two dimesnional =>
**DataFrame**

- one dimensional =>
- 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.

- Refer Here for the jupyter notebook.