by using this data i need answering those questions by using python language: Here is the summarized data of international students in Canada from different countries for the years $2021-2023$:

Country $202120222023$

Afghanistan $80170140$

Albania $305345545$

Algeria $316553607180$

Andorra $1050$

Angola $507565$

Anguilla $000$

Antigua and Barbuda $857580$

Argentina $585620530$

Armenia $556065$

Aruba $000$

Australia $360360395$

Austria $300235110$

Azerbaijan $2201803001-$ Explain your dataset briefly. What is your aim about this dataset. Read the dataset.

$2-$ List the first $10$ data.

$3-$ Find out how many data there are. Show the number of rows and columns.

$4-$ Display the number $0$ and $1$ in the predict column $($target column$).$

$5-$ Display data types of all parameters.

$6-$ Display statistical information about the data set.

$7-$ Display missing data in dataset.

$8-$ Suppose there is missing data in the dataset, show the solution to the problem

$9-$ Find the mean of any column of numerical data in the dataset

$10-$ Find the highest value in any column of numerical data in the dataset

$11-$ Find the mean value by grouping them according to the column of categorical data.

$12-$ Find how many different data are in the column consisting of categorical data.

$13-$ Draw the correlation matrix

$14-$ Decide about independent and dependent variables. Create your x and y$\text{'}$ variables in your dataset.

$15-$ Divide $($split$)$ the data set as test and train

$16-$ Apply normalization to the dataset.

$17-$ Apply one of the Machine Learning algorithms $($Random Forest or Support Vector Machine$)-$ Briefly explain the relevant algorithm you used in your project and what you understand from the algorithm.

$18-$ Create a confusion matrix

$19-$ Find the values of accuracy, sensitivity$,$ recall and f$1$ score. Make comment about the Accuracy score. Why do we find out these metrics, explain briefly.