Assignment Specification

Description: This assignment has two parts: processing $2$ csv files related to City Bike ridership for the

same month in different years and comparing the two files.

Part $1$:

Input: No input from the user required. The input file names to use in the script are NYC$-$CitiBike$-$Mar$17.$csv

and NYC$-$CitiBike$-$Mar$23.$csv

Please note:

file name has to be without its complete file path. For example: c:$/$stevens$/$em$624/$ NYC$-$CitiBike$-$

Mar$17.$csv is NOT right. If you change platform or move the file to another directory, the script

wouldn't work. Be sure your script and your file are in the same directory.

No data structure management library $($like pandas$)$ should be used for this assignment.

The two files use a slightly different structure. In the Mar$17$ one, user type is defined as "User Type",

and this can be "Subscriber" $($meaning users with a subscription$)$ or "Customer" $($meaning

occasional users$).$ In the Mar$23$ one, user type is defined as $"$ member$\_$casual" and this can be

"member" $($meaning users with a subscription$)$ or "casual" $($meaning occasional users$).$

Output: Skip a line$/$print a blank line, then print per each file:

The file has n lines $($ n $1$ will be for Mar$17,$ n $2$ for Mar$23).$ Of those n :

Mar$17$: x$1$ of them have "Customer" as usertype, $y1$ have "Subscriber" as usertype. "Customer"

are $z1\%$ of the total

Mar$23$: x$2$ of them have "casual" as member$\_$casual, $y2$ have "member" as member$\_$casual.

"casual" are $z2\%$ of the total

Procedure:

Open the files.

Loop into the files.

For each file:

a$.$ Count the number of lines $-$ Note: skip the header. You will get $2$ number: n $1$ for Mar$17$ and

n$2$ for Mar$23.$

b$.$ Count of the number of lines with: $($Mar$17)$ "Customer" as usertype $($this is $x1)$ or $($Mar$23)$

"casual" as member$\_$casual $($this is $x2).$

c$.$ Count of the number of lines with: $"($Mar$17)"$ Subscriber" as usertype $($this is $y1)$ or $($Mar$23)$

"member" as member$\_$casual $($this is y$2).$

d$.$ Calculate the z$1\%$ of "Customer" in Mar$17-$ Calculate the z$2\%$ of "casual" in Mar$23.$

e$.$ Print: The file has $n$ lines. Of those $x$ are occasional users, $y$ have a subscription. Occasional

users are $z\%$ of the total. Part $2$:

Input: No input from the user required. Use the data from Part $1$

Output: Comparison of the data in the $2$ files. Considering the files are related to different periods, we want

to compare them to optimize the bike availability. In particular, because one file is related to data before the

pandemic while the other is after, we want to evaluate the impact of the pandemic on the ridership.

Procedure:

Check IF n$1>$n$2$:

IF n$1>$n$2,$ print: The Mar$17$ riders are more than the Mar$23$

else, print: The Mar$23$ riders are more or equal than the Mar$17$

Check IF z$1>$z$2$:

IF z$1>$z$2,$ print: Before the pandemic there were more occasional users than after the

pandemic

else, print: After the pandemic there were more or equal occasional users than before the

pandemic

Write a $1$ page interpretation. The interpretation would be a narrative describing$/$explaining in

plain English the results of your Python script. It should NOT be a description of your code.

Submit the $3$ coding parts as a single $.$py file via Canvas and the interpretation in a separate doc$/$pdf file.