Create Numpy Arrays Using Functions in Hindi – Numpy In Hindi – Numpy Arrays Ko Ham Functions Ke Sath Bhi Create Kar Sakte Hain |
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Create Numpy Arrays Using Functions
Contents
Arrays Ko Functions Ke Sath Create Karne Ke Liye Koi Types Ke Functions Diye Gaye Hain Joki Alag Alag Tarah Se Numpy Arrays Ko Create Karte Hain.
- zeros
- ones
- eye
- diag
- randint
- rand
- randn
In Functions Ko Ham Ek Ek Karke Dekhne Wale Hai |
Zeros Functions In Hindi
Zeros Functions Ka Istemal karne Se Ham Numpy Zeros Array Create Kar Sakte Hai.
Example:
import numpy as np arr = np.zeros(2) print(arr)
Output:
array([0., 0.])
Ones Functions In Hindi
Ones Function Ka Istemal Karke Ham Numpy ones Array Create Kar Sakte Hai. Isme Keval 1 Number Honge |
Also Read – NumPy Creating Arrays
Example:
import numpy as np arr = np.ones(2) print(arr)
Output:
array([1., 1.])
Eye Functions In Hindi
Eye Function Ka Istemal Karke Aap Diagonal Matrix Create Kar Sakte Hai. Lekin Is Diagonal Matrix Elements Keval 1 Hoga And Ye 2-D Martix Create Karega |

Example:
import numpy as np arr = np.eye(4) print(arr)
Output:
array([[1., 0., 0., 0.], [0., 1., 0., 0.], [0., 0., 1., 0.], [0., 0., 0., 1.]])
Diag Functions In Hindi
Diag Function Ka Istemal Karke Aap Diagonal Matrix With Choices Number Ke Sath Create Kar Sakte Hain. Ye Input Me List Leta Hai |
Example:
import numpy as np ls = [1,2,3,4] arr = np.diag(ls) print(arr)
Output:
array([[1, 0, 0, 0], [0, 2, 0, 0], [0, 0, 3, 0], [0, 0, 0, 4]])
Randint Functions In Hindi
randint Functions Ka Istemal Karke Ham Random Number Matrix Create Kar Sakte Hai.
Isme Ham 3 Value Pass Karte Hai – Low , High , Number
Example:
import numpy as np arr = np.random.randint(1,10,5) print(arr)
Output:
array([6, 2, 5, 7, 2])
Rand Functions In Hindi
Rand Function ka Istemal karke Ham random Floating 0 or 1 Ke Bich Me Generate Kara Sakte Hai |
Example:
import numpy as np arr = np.random.rand(5) print(arr)
Output:
array([0.52580758, 0.41356057, 0.19416662, 0.2760978 , 0.12535946])
Randn Functions In Hindi
Randn Functions Ka Istemal Karke Standard Number Zero ke Bich me Create Kar Sakte Hai Or Fir Aap Iska Mean Nikal Sakte Hain And Isme Negative Or Positive Number Dono Honge |
Example:
import numpy as np arr = np.random.randn(5) print(arr)
Output:
array([ 0.25505529, 1.00033365, -0.98209137, -0.75438967, 0.91431776])
Also Read – NumPy – Environment + Setup + Anaconda
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