# 3.1.3. Exercises¶

Tip

Copy this into your Class Notes repo and solve it there. You can find answers here after you try the problems.

```import numpy as np
```

## 3.1.3.1. Some problems. Put your answers inside the print functions¶

```a = np.arange(4).reshape((2,2))
print("array a:")
print(a)

print("\nMaximum value of a:")
print() # put your answer inside the print

print("\nMinimum value of a:")
print() # put your answer inside the print

print("\nReturn an array of the max in each column of a:")
print()

print("\nReturn an array of the min in each row of a:")
print()

print("\nReturn a, sorted within each row:")
print()

print("\nReturn a, sorted within each column:")
print()
```
```array a:
[[0 1]
[2 3]]

Maximum value of a:

Minimum value of a:

Return an array of the max in each column of a:

Return an array of the min in each row of a:

Return a, sorted within each row:

Return a, sorted within each column:
```
```b = np.arange(40).reshape((20,2))
print("array b:")
print(b)

print("\nPrint elements of the first column of b above that column's 80th percentile:")
print()

print("\nCovariance matrix of the columns of b:")
print()
```
```array b:
[[ 0  1]
[ 2  3]
[ 4  5]
[ 6  7]
[ 8  9]
[10 11]
[12 13]
[14 15]
[16 17]
[18 19]
[20 21]
[22 23]
[24 25]
[26 27]
[28 29]
[30 31]
[32 33]
[34 35]
[36 37]
[38 39]]

Print elements of the first column of b above that column's 80th percentile:

Covariance matrix of the columns of b:
```