create a numpy array from a list

import numpy as np
List=[1,2,3,4]
a1=np.array(List)
print(a1)

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access individual elements from array

import numpy as np
List=[1,2,3,4]
a1=np.array(List)
print(a1[0])

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another example of accessing elements from numpy array

import numpy as np
a7=np.array([[10,11,12,13],[21,22,23,24]])
print(a7[1,3])
print(a7[1][3])

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type of ndarray, shape and itemsize of ndarray

import numpy as np
a1=np.array([1,2,3,4])
a2=np.array([[2,4,6],[1,3,5]])
print(type(a1),type(a2))
print(a1.shape)
print(a2.shape)
print(a2.itemsize)

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adding number to each element of ndarray

import numpy as np
a1=np.array([1,2,3,4])
a1=a1+2
print(a1)

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create ndarray from tuple

import numpy as np
a1=np.array((1,2,3,4))
print(a1)

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create ndarray from dictionary

import numpy as np
dict1={1:'A',2:'B',3:'C'}
a1=np.array(dict1)
print(a1)

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create ndarray using fromiter function

import numpy as np
dict1={1:'A',2:'B',3:'C'}
a1=np.fromiter(dict1,dtype=np.int32)
print(a1[0])

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create ndarray from string using fromiter function

import numpy as np
str="HelloWorld"
a1=np.fromiter(str,dtype="U2")
print(a1)

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create ndarray with a numerical range using arange()

import numpy as np
ar5=np.arange(7)
print(ar5)

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create array with a numerical range using linspace()

import numpy as np
a1=np.linspace(2,10,5)
print(a1)

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create 2d ndarray using array()

import numpy as np
List1=[[1,3,5],[2,4,6]]
nd2=np.array(List1)
print(nd2)
print(nd2.shape)

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create 2d ndarray using arrange and reshape the ndarray

import numpy as np
ar=np.arange(10)
print(ar)
ar1=ar.reshape(5,2)
print(ar1)
ar2=ar.reshape(2,5)
print(ar2)

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create ndarray and reshape in single statement

import numpy as np
ar=np.arange(10).reshape(5,2)
print(ar)

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create empty array using empty() function array will contain garbage values

import numpy as np
ar=np.empty(3)
print(ar)

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create ndarray containing zero values using zeros function

import numpy as np
ar=np.zeros(3)
print(ar)

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crate ndarray containing one using ones function

import numpy as np
ar=np.ones(3)
print(ar)

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access 3rd element from ndarray

import numpy as np
ar=np.array([3,4,5,7,8])
print(ar[2])

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access individual elements in 2d array

import numpy as np
ar=np.array([[3,4,5,7,8],[1,2,3,4,5]])
print(ar[1][2])

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array slices

import numpy as np
ar=np.array([3,4,5,7,8,1,2,3,4,5])
print(ar[2:5])

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array slice step=2

import numpy as np
ar=np.array([3,4,5,7,8,1,2,3,4,5])
print(ar[2:5:2])

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combine two ndarray horizontally using hstack function

import numpy as np
ar=np.array([1,2,3])
ar1=np.array([4,5,6])
ar2=np.hstack((ar,ar1))
print(ar2)

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combine two ndarray vertically using vstack function

import numpy as np
ar=np.array([1,2,3])
ar1=np.array([4,5,6])
ar2=np.vstack((ar,ar1))
print(ar2)

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concatenate two ndarray using concatenate function

import numpy as np
ar=np.array([1,2,3])
ar1=np.array([4,5,6])
ar2=np.concatenate((ar,ar1))
print(ar2)

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hsplit function

import numpy as np
ar=np.arange(24.0).reshape(4,6)
print(ar)
ar1=np.hsplit(ar,2)
print(ar1)

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vsplit function

import numpy as np
ar=np.arange(24.0).reshape(4,6)
print(ar)
ar1=np.vsplit(ar,2)
print(ar1)

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split function

import numpy as np
ar=[10,11,12,13,14,15,16,17,18,19]
ar1=np.split(ar,[2,6])
print(ar1)


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extract elements using a condition

import numpy as np
ar=[10,11,12,13,14,15,16,17,18,19]
cond1=np.mod(ar,5)==0
ar1=np.extract(cond1,ar)
print(ar1)

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add two ndarrays using + operator

import numpy as np
ar1=np.array([10,11,12,13,14])
ar2=np.array([15,16,17,18,19])
ar3=ar1+ar2
print(ar3)

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-,*,/,% operators

numpy.add
numpy.subtract
multiply
divide
mod
remainder

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