Python For Data Science

The learning objectives of this section are: Manipulating arrays and Performing operations on array

EnrollThe learning objectives of this section are:

- Manipulate arrays
- Reshape and Resize arrays
- Stack arrays
- Transposing
- Swapaxis

- Perform operations on arrays
- Perform basic mathematical operations
- Broadcast Numpy
- Apply built-in functions
- Expressing Conditional Logic

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

OUTPUT:

```
[[ 1 2 3 4]
[ 5 6 7 8]
[ 9 10 11 12]]
```

`print(arr.shape)`

OUTPUT:

`(3,4)`

```
sh_arr=arr.reshape(12,1)
sh_arr
```

OUTPUT:

```
array([[ 1],
[ 2],
[ 3],
[ 4],
[ 5],
[ 6],
[ 7],
[ 8],
[ 9],
[10],
[11],
[12]])
```

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

OUTPUT:

```
array([[1, 2, 3, 4],
[5, 6, 7, 8]])
```

```
arr.resize(6,6,refcheck=False)
arr
```

OUTPUT:

```
array([[1, 2, 3, 4, 5, 6],
[7, 8, 0, 0, 0,0],
[0, 0, 0, 0, 0,0],
[0, 0, 0, 0, 0,0],
[0, 0, 0, 0, 0,0],
[0, 0, 0, 0, 0,0]])
```

`np.hstack()`

and `n.vstack()`

Stacking is done using the `np.hstack()`

and `np.vstack()`

methods. For horizontal stacking, the number of rows should be the same, while for vertical stacking, the number of columns should be the same.

```
a = np.array([1, 2, 3,4,5])
b = np.array([4, 5, 6,7,8])
c = np.array([4, 5, 6])
np.hstack([a,b,c])
```

OUTPUT:

`array([1, 2, 3, 4, 5, 4, 5, 6, 7, 8, 4, 5, 6])`

```
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
c = np.array([4, 5, 6])
np.vstack((a,b,c))
```

OUTPUT:

```
array([[1, 2, 3],
[4, 5, 6],
[4, 5, 6]])
```

```
a=np.array([[1,2,3,4],[5,6,7,8]])
a
```

OUTPUT:

`array([[1, 2, 3, 4], [5, 6, 7, 8]])`

`a.shape`

OUTPUT:

`(2,4)`

```
flat_array = a.flatten()
flat_array
```

OUTPUT:

`array([1, 2, 3, 4, 5, 6, 7, 8])`

`flat_array.shape`

OUTPUT:

`(8,)`

```
arr = np.array([[1,2,3,4],[5,6,7,8]])
arr
```

OUTPUT:

```
array([[1, 2, 3, 4],
[5, 6, 7, 8]])
```

`arr.shape`

OUTPUT:

`(2,4)`

```
arr1= arr.transpose(1,0)
arr1.shape
```

OUTPUT:

`(4,2)`

`arr1`

OUTPUT:

```
array([[1, 5],
[2, 6],
[3, 7],
[4, 8]])
```

```
arr = np.arange(10).reshape((5,2))
arr
```

OUTPUT:

```
array([[0, 1],
[2, 3],
[4, 5],
[6, 7],
[8, 9]])
```

`np.sum(arr)`

OUTPUT:

`45`

`print(np.sum(arr,axis =0)) ## rows `

OUTPUT:

`[20 25]`

`print(np.sum(arr,axis =1))`

OUTPUT:

`[ 1 5 9 13 17]`

```
a = np.arange(10)
a
```

OUTPUT:

`array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])`

```
# condition , yes , no
b = np.where(a > 5, a, 10*a)
b
```

OUTPUT:

`array([ 0, 10, 20, 30, 40, 50, 6, 7, 8, 9])`

```
arr = np.array([3,4,1,5,9,6,2])
print(arr)
arr_sorted = sorted(arr,reverse=False)
print(arr_sorted)
```

OUTPUT:

```
[3 4 1 5 9 6 2]
[1, 2, 3, 4, 5, 6, 9]
```

```
array1 = np.array([10,20,30,40,50])
array2 = np.array([2])
print(array1/array2)
```

OUTPUT:

`[ 5. 10. 15. 20. 25.]`

```
array1 = np.array([[10,20,30,40,50],[10,20,30,40,50]])
array2 = np.array([1,2,3,4,5])
print(array1+array2)
```

OUTPUT:

```
[[11 22 33 44 55]
[11 22 33 44 55]]
```

Lesson Assignment

Challenge yourself with our lab assignment and put your skills to test.

```
# Python Program to find the area of triangle
a = 5
b = 6
c = 7
# Uncomment below to take inputs from the user
# a = float(input('Enter first side: '))
# b = float(input('Enter second side: '))
# c = float(input('Enter third side: '))
# calculate the semi-perimeter
s = (a + b + c) / 2
# calculate the area
area = (s*(s-a)*(s-b)*(s-c)) ** 0.5
print('The area of the triangle is %0.2f' %area)
```

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