# NumPy Array Shape And Reshape – Numpy In Hindi

NumPy Array Shape And Reshape in HindiNumpy In Hindi – Is Post Me Numpy Shape() And reshape() Function Ke Bare Me Baat Karne Wale Hain |

## NumPy Array Shape And Reshape in Hindi

Contents

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Numpy Ke In Dono Function Ko Ham Ek Ek Karke Understand Karte Hai Or Fir Inke Example Bhi Dekh Te Hai.

### NumPy Array Shape in Hindi

Shape Function Ka Istemal Numpy Arrays Ke Row And Column Ko Find Karne Ke Liye Istemal Kiya Jata Hai |

Shape Function Return Me Ek Tuple Deta Hai |

Example:

```import numpy as np
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
print(arr.shape)```

Output:

`(2, 4)`

Example 2:

```import numpy as np
arr = np.array([[[1,2,3]]])
print(arr.shape)```

Output:

`(1, 1, 3)`

### NumPy Array Reshape in Hindi

Reshape() Function Ka Istemal Keval shape Ko Reshape Karne Ke Liye Hota Hai Yani Ki reshape Function Old Shape Me Changing Karta Hai |

Example From 1-D Array To 2-D Array:

Hamare Pass Ek 1-D Array Hai Or Usme 10 Elements Hai Ab Hamne reshape Karke bola hai ki 2 Column Or Har Ek Column Me 5 Elements |

```import numpy as np
arr = np.array([1,2,3,4,5,6,7,8,9,10])
newshape = arr.reshape(2,5)
print(newshape)```

Output:

```[[ 1  2  3  4  5]
[ 6  7  8  9 10]]```

Example2: From 1-D Array To 3D Array

Ham 1-D array se 3-D Array me Convert Karne Wale Hai. Hamare Pass Ek arr 1D Array hai Or Ab Hamne reshape Karke 2 Array Or 3 Column And 2 Row Create Ki Hai |

```import numpy as np
arr = np.array([1,2,3,4,5,6,7,8,9,10,11,12])
newarr = arr.reshape(2,3,2)
print(newarr)```

Output:

```[[[ 1  2]
[ 3  4]
[ 5  6]]

[[ 7  8]
[ 9 10]
[11 12]]]```

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