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Matplotlib And Numpy Libraries In Python Language

By Author: saketh varma
Total Articles: 3


Matplotlib of the Python programming language is used in data science technology when our data is stored in two-dimensional form and we want to process it in two-dimensional form. There is a module present in the Matplotlib which is known as pyplot. This module provides various features which help in performing operations on the data. The Matplotlib uses different types of graphs for storing and representing the data; for example, bar charts, error charts, histogram, power spectra, etc.

The NumPy library in python programming language stands for numerical python. In the NumPy library, multidimensional arrays are created. In data science technology, this library is mostly used for performing logical and arithmetic operations on the arrays. It has been said that NumPy library can be used along with other libraries of python as an alternative to the MATLAB.

Here are some operations performed on the data which is stored in the arrays for which Numpy is used ->
• For performing logical and arithmetic operations on the data.
• For performing Fourier transforms on the data.
• For performing shape manipulation on the data.
• For performing linear algebra on the data.
• For generating random numbers.

Python is an object-oriented programming language and we know that in object-oriented programming languages the data is stored in the objects instead of variables. In Python programming language, arrays are treated as an object. As said above, the NumPy library is used to create multidimensional arrays. The most common array which is created here is N-dimensional array, also known as ndarray. This data structure is used to store the data with the same data type. The indexing of ndarrays starts with zero.

Whenever the data is stored in any data structure, that data allocates space in the memory. In ndarray, all the data which is stored allocates the same size in the memory.

If we want to create ndarray in our program, we should call the numpy.array function. In the technical language, when we use a function, we say we called a function. This function is a parametric function and takes the parameters--> object, dtype, copy, order, subok, ndmin. The syntax of this function is as follows-->
Numpy.array (object, dtype=none, copy= true, order= none, subok= false, ndmin=0)

Here are some data types which are used in the NumPy library of the Python language. They are listed below-->

• bool
It stores Boolean values, true and false.
• Int
It stores Integer values.
• int8
It stores the Byte values. Its range is from –128 to 127.
• int16
It stores the Integer values. Its range is from –32768 to 32767.
• int64
It also stores the Integer values, but its range is from -2147483648 to 2147483647.

There are many more. I have listed a few of them.

Those who are interested in acquiring more knowledge about the Python programming language can enroll themselves in python training in Pune at the mentioned link.

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