Part A: Code such python properly imports the provided dataset and as part of code provided as output should provide the info summary that shows column names and the Dtypes as was shown in similar class example.

Code & Output needed: PROVIDE the Code then provide the appropriate output of the info summary so that it shows a complete summary of the columns information and what "Dtype" was assigned for each can be reviewed from the student's supplied output. No changes should be made to any columns in this part $A.$

Part B: PROVIDE the Code then appropriate output for the following:

Complete the Code necessary to correct the Dtype for any categorical variable$/$column that show "object" but leave any the numerical columns$/$variables alone $($avoid changing any columns that show int$64$ or float$64)$ ; they should stay the same as they were imported since this HW is concentrating only on categorical variables$/$columns$.$

Code & OUTPUT: As output provides an updated info summary that shows column names and the Dtypes as was shown in similar class examples. and make sure those incorrect DTypes required to be updated in this part $B$ are in fact completed in your output done via your code, thus reflecting all proper corrections per instructions given in this part.

Part C: Create a relative frequency Table for the column that contains: Industry Type

Code & OUTPUT: PROVIDE the Code before then providing the output of the frequency table including proper title $($reminder all titles should be showing student's name at the end of the title$)$