PROMPTS.md

Exercises tips and tricks

1. Understanding the Data

1.1 Import data and show first 5 rows of the dataframe

Chat prompt: @workspace /newNotebook create a notebook called "COVID19 Worldwide Testing Data" that imports the tested_worldwide.csv at root level and display the first 5 rows

NOTE: In case you get an error related to "pandas library not found", use copilot to help you fixing it:

1.2 Display the number of rows and columns in the dataframe.

1.3 Display the data types of each column

1.4 Display the number of missing values in each column

1.5 Display the number of unique values in each column

2. Data Cleaning

2.1 Drop the columns that are not needed for the analysis

2.2 Rename the columns to make them more readable

2.3 Drop the rows that have missing values

2.4 Convert the data types of the columns to the appropriate types

Notice that I have first used the chat, then copilot inline to complete the coversion for the column "Country".

2.5 Display the number of missing values in each column

3. Extracting the Top Ten Countries with Most Covid-19 Cases

3.1 Create a new dataframe that contains the total number of positive cases for each country

3.2 Sort the dataframe in descending order of the total number of positive cases

3.3 Display the top ten countries with the most positive cases

4. Identifying the Highest Positive Against Tested Cases

4.1 Create a new dataframe that contains the total number of tests conducted for each country

4.2 Sort the dataframe in descending order of the total number of tests conducted

4.3 Display the top ten countries with the most tests conducted

5. Identifying top three countries that have had the highest number of positive cases against the number of tests carried out

5.1 Merge the two dataframes created in the previous steps

5.2 Create a new column that contains the ratio of positive cases to the number of tests conducted

5.3 Sort the dataframe in descending order of the ratio of positive cases to the number of tests conducted

5.4 Display the top three countries with the highest ratio of positive cases to the number of tests conducted

6. Displaying the Results

6.1 Display the results a chart that shows the top three countries with the highest ratio of positive cases to the number of tests conducted

NOTE: In case you get an error related to "ImportError with matplotlib", use copilot inline to help you fixing it:

And then, if the module is not found, use copilot chat to help you fixing it:

6.2 Display the results in a chart that shows the top ten countries with the most positive cases

6.3 Display the results in a chart that shows the top ten countries with the most tests conducted