In performing the tasks in this assignment, consider the sales data and advertising expenses from January to December:

Month AdExp Sales

Jan $165000$

Feb $20\mathrm{.}714000$

Mar $26\mathrm{.}536000$

Apr $30\mathrm{.}640000$

May $32\mathrm{.}349000$

Jun $29\mathrm{.}57000$

Jul $28\mathrm{.}352000$

Aug $31\mathrm{.}365000$

Sep $32\mathrm{.}217000$

Oct $26\mathrm{.}45000$

Nov $23\mathrm{.}417000$

Dec $16\mathrm{.}41000$

Task $1$

Create a dictionary of the sales data using $$Month$$ as index.

Task $2$

Create a pandas series using the sales dictionary created above.

i$)$ Print all the months from the series.

ii$)$ Print all the sales value from the series.

iii$)$ Print the sales for the last $6$ months $($Jul$-$Dec$).$

iv$)$ Change the sales for Jun to $11000$ in the series object.

v$)$ Display all months when sales was above $30000.$

vi$)$ Find the average sales for the $12$ months.

vii$)$ There has been additional sale of $2500,4800$ and $3900$ in the month of Aug, Sep and Oct respectively. Create a series of this additional sales for the mentioned months. Find the total sales across the months considering the additional sales.

viii$)$ Display the months with minimum and maximum sales $($consider the additional sales given in $$vii$.$

Task $3$

Create a numpy array using the original data given above for AdExp and Sales.

Task $4$

Using the numpy array in Task $3,$ create a dataframe with months as index and the given column names above.

i$)$ Select and display the AdExp and Sales values for Mar, Apr and May.

ii$)$ Select and display AdExp for Nov.

iii$)$ Select and display Sales for Feb.

iv$)$ Create a new column "Net$\_$Sales" which is the difference of Sales and AdExp $($Sales $-$AdExp$).$

v$)$ Find the average value of "AdExp", "Sales" and "Net$\_$Sales".

vi$)$ Find the sum of Sales for the $12$ months.

vii$)$ Get the min, max, median, standard deviation, $25$ percentile value, $75$ percentile value and the average of "AdExp", "Sales" and "Net$\_$Sales" using a single function.

viii$)$ Sort the data by Sales in descending order and display.

ix$)$ Include the index as a column in the dataframe. Change the column name to "Month". Hint: Use the reset$\_$index$()$ and rename$()$ function.

x$)$ Write the data into a csv file "Sale.csv$".$ Exclude the index while writing into the file.