Expert answer:program 6 code

Expert answer:please read the instructions and do what you have to do. if you have any questions please let me know.
program_6_instructions.pdf

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12/3/2017
CSCI 127, Program 6
Program 6: Data Visualization
Logistics
Due Date: Friday, December 8th no later than midnight.
Partner Information: You may complete this assignment individually or with exactly one partner. If you
work with a partner, you must both be enrolled in the same lab section or you will both lose 10 points.
Submission Instructions: Upload your solution, renamed to YourFirstName-YourLastNamePartnerFirstName-PartnerLastName.py to the BrightSpace Program 6 Dropbox. If you work with a
partner, only one person should submit the solution. However, to avoid losing 10 points, write both names
in the BrightSpace Dropbox comment box.
Deadline Reminder: Once the submission deadline passes, BrightSpace will no longer accept your Python
submission and you will no longer be able to earn credit. Thus, if you are not able to fully complete the
assignment, submit whatever you have before the deadline so that partial credit can be earned.
Learning Outcomes
Use pandas to visualize data.
Gain experience visualizing data in an insightful manner.
Design and implement a solution to a problem with no starting code.
Background
In 2013, Montana State University assembled this Pre-Disaster Mitigation Plan.
The file buildings.csv is a comma-separated values representation of Table 3.4-1, MSU-Bozeman Building
Characteristics. This table appears on pages 24-28 of the Pre-Disaster Mitigation Plan.
Assignment
Use pandas to produce two different visualizations that help the user gain insight into the information
contained in buildings.csv.
Input File Description
The first line contains the column labels. To learn more about any particular label, refer to the Pre-Disaster
Mitigation Plan.
Each subsequent line contains information about a particular building on the MSU campus.
Grading – 100 points
20 points – pandas is used to produce the visualizations (all or nothing).
10 points – Each visualization is a different type. For example, one visualization could be a bar chart and
the other could be a pie chart (all or nothing).
10 points – The visualizations use the underlying data to show different things (all or nothing).
20 points – All aspects of each visualization are clearly labeled (3 points for each type of improvement up
to 20 points).
10 points – The first visualization is insightful (-2 if 1/3 of the other submissions are more interesting and
-5 if 2/3 of the other submissions are more interesting).
https://www.cs.montana.edu/paxton/classes/csci127/programs/program6/
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12/3/2017
CSCI 127, Program 6
10 points – The second visualization is insightful (-2 if 1/3 of the other submissions are more interesting
and -5 if 2/3 of the other submissions are more interesting).
20 points – The Python solution is properly commented, easy to understand and does not contain
unnecessary code. (3 points for each type of improvement up to 20 points.)
Honor’s Lab
The points you earn from the grading scale above will be multiplied by .9 for a maximum of 90 points.
The other 10 points can be earned by adding a third insightful visualization. The type of this third
visualization should be different from the others. In addition, the third visualization should use the
underlying data to show something different.
https://www.cs.montana.edu/paxton/classes/csci127/programs/program6/
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