kopia lustrzana https://github.com/animator/learn-python
commit
165639d661
|
@ -3,6 +3,7 @@
|
|||
- [Installing NumPy](installing-numpy.md)
|
||||
- [Introduction](introduction.md)
|
||||
- [NumPy Data Types](datatypes.md)
|
||||
- [Numpy Array Shape and Reshape](reshape-array.md)
|
||||
- [Basic Mathematics](basic_math.md)
|
||||
- [Operations on Arrays in NumPy](operations-on-arrays.md)
|
||||
- [Loading Arrays from Files](loading_arrays_from_files.md)
|
||||
|
|
|
@ -0,0 +1,57 @@
|
|||
# Numpy Array Shape and Reshape
|
||||
|
||||
In NumPy, the primary data structure is the ndarray (N-dimensional array). An array can have one or more dimensions, and it organizes your data efficiently.
|
||||
|
||||
Let us create a 2D array
|
||||
|
||||
``` python
|
||||
import numpy as np
|
||||
|
||||
numbers = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
|
||||
print(numbers)
|
||||
```
|
||||
|
||||
#### Output:
|
||||
|
||||
``` python
|
||||
array([[1, 2, 3, 4],[5, 6, 7, 8]])
|
||||
```
|
||||
|
||||
## Changing Array Shape using `reshape()`
|
||||
|
||||
The `reshape()` function allows you to rearrange the data within a NumPy array.
|
||||
|
||||
It take 2 arguments, row and columns. The `reshape()` can add or remove the dimensions. For instance, array can convert a 1D array into a 2D array or vice versa.
|
||||
|
||||
``` python
|
||||
arr_1d = np.array([1, 2, 3, 4, 5, 6]) # 1D array
|
||||
arr_2d = arr_1d.reshape(2, 3) # Reshaping with 2 rows and 3 cols
|
||||
|
||||
print(arr_2d)
|
||||
```
|
||||
|
||||
#### Output:
|
||||
|
||||
``` python
|
||||
array([[1, 2, 3],[4, 5, 6]])
|
||||
```
|
||||
|
||||
## Changing Array Shape using `resize()`
|
||||
|
||||
The `resize()` function allows you to modify the shape of a NumPy array directly.
|
||||
|
||||
It take 2 arguements, row and columns.
|
||||
|
||||
``` python
|
||||
import numpy as np
|
||||
arr_1d = np.array([1, 2, 3, 4, 5, 6])
|
||||
|
||||
arr_1d.resize((2, 3)) # 2 rows and 3 cols
|
||||
print(arr_1d)
|
||||
```
|
||||
|
||||
#### Output:
|
||||
|
||||
``` python
|
||||
array([[1, 2, 3],[4, 5, 6]])
|
||||
```
|
Ładowanie…
Reference in New Issue