Pandas Tutorial for Beginners with 20 Exercises | Part 1

In this tutorial, we’ll cover the basics of Pandas and walk you through 20 exercises designed to help you master the library. We’ll start with an introduction to the Pandas library and its key data structures, including Series and DataFrame. Then, we’ll dive into the fundamentals of data manipulation with Pandas, covering topics like filtering, sorting, and merging data.

1. Import the numpy package under the name np(★☆☆)

import numpy as np

2. Print the numpy version and the configuration (★☆☆)

print(np.version)
np.show_config()

3. Create a null vector of size 10 (★☆☆)
Z = np.zeros(10)
print(Z)

4. How to get the documentation of the numpy add function from the command
line? (★☆☆)

python -c "import numpy; numpy.info(numpy.add)"

5. Create a null vector of size 10 but the fifth value which is 1 (★☆☆)

Z = np.zeros(10)
Z[4] = 1
print(Z)

6. Create a vector with values ranging from 10 to 49 (★☆☆)

Z = np.arange(10,50)
print(Z)

7. Reverse a vector (first element becomes last) (★☆☆)

Z = np.arange(50)
Z = Z[::-1]

8. Create a 3×3 matrix with values ranging from 0 to 8 (★☆☆)

Z = np.arange(9).reshape(3,3)
print(Z)

9. Find indices of non­zero elements from 1,2,0,0,4,0 (★☆☆)

nz = np.nonzero([1,2,0,0,4,0])
print(nz)

10. Create a 3×3 identity matrix (★☆☆)

Z = np.eye(3)
print(Z)

11. Create a 3x3x3 array with random values (★☆☆)

Z = np.random.random((3,3,3))
print(Z)

12. Create a 10×10 array with random values and find the minimum and maximum
values (★☆☆)

Z = np.random.random((10,10))
Zmin, Zmax = Z.min(), Z.max()
print(Zmin, Zmax)

13. Create a random vector of size 30 and find the mean value (★☆☆)

Z = np.random.random(30)
m = Z.mean()
print(m)

14. Create a 2d array with 1 on the border and 0 inside (★☆☆)

Z = np.ones((10,10))
Z[1:-1,1:-1] = 0

15. What is the result of the following expression? (★☆☆)

0 * np.nan
np.nan == np.nan
np.inf > np.nan
np.nan - np.nan
0.3 == 3 * 0.1

16. Create a 5×5 matrix with values 1,2,3,4 just below the diagonal (★☆☆)

Z = np.diag(1+np.arange(4),k=-1)
print(Z)

17. Create a 8×8 matrix and fill it with a checkerboard pattern (★☆☆)

Z = np.zeros((8,8),dtype=int)
Z[1::2,::2] = 1
Z[::2,1::2] = 1
print(Z)

18. Consider a (6,7,8) shape array, what is the index (x,y,z) of the 100th element?

print(np.unravel_index(100,(6,7,8)))

19. Create a checkerboard 8×8 matrix using the tile function (★☆☆)

Z = np.tile( np.array([[0,1],[1,0]]), (4,4))
print(Z)

20. Normalize a 5×5 random matrix (★☆☆)

Z = np.random.random((5,5))
Zmax, Zmin = Z.max(), Z.min()
Z = (Z - Zmin)/(Zmax - Zmin)
print(Z)