Q:$1($Answer$)$

import pandas as pd

def import$\_$data$($csv$\_$filename$)$:

$"""$

Import data from a CSV file into a pandas DataFrame.

Parameters:

csv$\_$filename $($str$)$: File path for the CSV file.

Returns:

pandas.DataFrame: DataFrame containing the imported data.

$"""$

# Read the CSV file into a DataFrame

df $=$ pd$.$read$\_$csv$($csv$\_$filename, sep$=",",$ header$=0,$ index$\_$col$=$None$)$

return df

# Example usage:

df $=$ import$\_$data$("$superstore$\_$data.csv$")$

print$($df$.$head$())$ # Display the first few rows of the DataFrame

Question: $4($Answer$)$

import pandas as pd

def compute$\_$profit$\_$per$\_$dollar$\_$sold$($df$)$:

# Calculate profit per dollar sold

df$[\text{'}$profit$\_$per$\_$dollar$\_$sold'$]=$ df$[\text{'}$Profit$\text{'}]/$ df$[\text{'}$Sales$\text{'}]$

# Return the dataframe with the new column

return df

# Example of usage:

# Assuming df is your pandas dataframe with columns "Profit" and "Sales"

new$\_$df $=$ compute$\_$profit$\_$per$\_$dollar$\_$sold$($df$)$

Question $5$:

Objective: Compute statistics on a variable$/$column Create a function called compute$\_$mean value that receives as input two arguments: a dataframe and the name of a column. If the column refers to a numeric type $($int$64$ or f loat$64),$ it should return the column average otherwise return a $-1.$ Return the average rounded to two decimals. Hint: E$.$g$.,$ to check if column Profit in the dataframe from question $1$ is of type float$64,$ use df$[$Profit$].$dtype$==$float$64$ Example of usage: mean$\_$value $=$ compute$\_$mean$($new$\_$df$,$ "Profit"$),$ where new$\_$df is the dataframe from question $4$ should return $28\mathrm{.}66.$

mean$\_$value $=$ compute$\_$mean$($df$,$ "Product Name"$),$ where new$\_$df is the dataframe from question $4$ should return $-1.$

Answer questions $5$ separately using the question answers from q$1$ and Q$4$