## numpy.ogrid function with example in python

numpy.ogrid(): This function returns mesh-grid ndarrays with only one dimension :math:neq 1 numpy.ogrid = <numpy.lib.index_tricks.OGridClass object> nd_grid instance which returns

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# Category: Numpy Tutorial

## numpy.ogrid function with example in python

## numpy.mgrid function with example program in python

## numpy.geomspace() function with example program in python

## numpy.logspace() function with example in python

## How to use the NumPy linspace function with examples | 2019

## numpy.arange() function with example in python | 2019

## numpy.random.standard_normal() function with example in python

## numpy.random.randint() function with example in python

## numpy.random.randn() function with example in python | 2019

## numpy.trim_zeros () Function with example in python

Numpy Stands for Numerial Python. It is special python programming package for data science projects. It is used to operate high level mathematical with arrays and matrices. It was developed by Jim Hugunin.

• It has powerful n dimensional arrays

• It execute very fast.

• It used less memory for variable storage

• It’s Mainly useful for linear algebra, Fourier transform and random numbers

Installation of Numpy Package:

You need to install by using pip command. Execute the below command to install numpy package.

**python -m pip install –user numpy**

Get started with numpy:

You need to import numpy package in your program to take advantage of numpy.

Import numpy as np

After importing numpy library you can call functions with np object.

numpy.ogrid(): This function returns mesh-grid ndarrays with only one dimension :math:neq 1 numpy.ogrid = <numpy.lib.index_tricks.OGridClass object> nd_grid instance which returns

Continue readingnumpy.mgrid function(): This funtion returns mesh-grid ndarrays all of the same dimensions numpy.mgrid = <numpy.lib.index_tricks.MGridClass object>¶ nd_grid instance which returns

Continue readingnumpy.geomspace(): This function return numbers spaced evenly on a log scale (a geometric progression). Syntax: numpy.geomspace(start, stop, num=50, endpoint=True, dtype=None,

Continue readingnumpy.logspace(): This function return numbers spaced evenly on a log scale. Syntax: numpy.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, axis=0) In

Continue readingnumpy.linspace(): This function Return evenly spaced numbers over a specified interval and num evenly spaced samples, calculated over the interval

Continue readingnumpy.arange() : If you want generate a sequence of numbers, arange() function is very helpful. It has regular range of

Continue readingnumpy.random.standard_normal(): This function draw samples from a standard Normal distribution (mean=0, stdev=1). Syntax: numpy.random.standard_normal(size=None) Parameters: size : int or tuple

Continue readingnumpy.random.randint() function: This function return random integers from low (inclusive) to high (exclusive). Return random integers from the “discrete uniform”

Continue readingnumpy.random.randn() function: This function return a sample (or samples) from the “standard normal” distribution. If positive, int_like or int-convertible arguments

Continue readingnumpy.trim_zeros(): This function trim the leading and/or trailing zeros from a 1-D array or sequence. syntax: numpy.trim_zeros(filt, trim=’fb’)[source] Parameters: filt

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