Congratulations on joining the Build Mania :: A Data Analysis Challenge! NASSCOM FutureSkills Prime, KPR Institute of Engineering & Technology and Open Weaver are proud to present this interesting practical challenge!
This challenge is open to all students of KPRIET who have completed the NASSCOM FutureSkills Prime course on Acquiring Data. Having completed this course, you must now be familiar with the concepts of Data Acquisition, Data Analysis and Data Validation. The Build Mania Challenge is designed to provide you an opportunity to apply these concepts and build industry-relevant Data Solutions.
Challenge Highlights
- This is a challenge ONLY for KPRIET Students and Faculty - You may participate individually or in groups (max 5 members in a group).
- This challenge focusses on applying your Data Analysis and Data Manipulation skills using “Pandas”, a popular open-source library for data analysis.
- The challenge consists of two parts, PART 1 - Coding Exercises and PART 2 - Application Development.
- Use kandi as a resource to support you through the challenge!
- CHALLENGE TIMELINE - Starts on Friday, 20th January 2023 and ends on Sunday, 12th February 2023.
- SUBMISSION DEADLINE - All responses need to be submitted by 10 pm on Sunday, 12th February 2023.
This challenge has been divided into two parts.
PART 1 - CODING EXERCISES
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For each of the questions below, submit a screenshot of the code and the corresponding output in the Challenge Submission Form.
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You may use kandi to search for code snippets to help you complete the exercises.
CLICK HERE to watch a 5 min video on how to search for code snippets and complete these coding exercises!
Before you begin, create a csv of your favourite sports team containing the following data with column headers - {Name, Country, Sport, Age, Gender, World_Ranking, No_of_Matches_Played} containing minimum five rows.
Q1. Read this csv using Pandas and save it into a DataFrame called df_1 and rename the column header of any 2 columns of the DataFrame. Submit a screenshot of the code and the corresponding output.
Q2. Using the Pandas library on the above DataFrame, find the average age of players in the team. Submit a screenshot of the code and the corresponding output.
Q3. For the above DataFrame, drop the last 2 rows. Submit a screenshot of the code and the corresponding output.
Q4. Move the column World_Ranking from index 6 to column index 2. Submit a screenshot of the code and the corresponding output.
Q5. Sort the DataFrame based on descending order of No_of_Matches_Played. Submit a screenshot of the code and the corresponding output.
Q6. Save this sorted DataFrame df_1 to a CSV file. Submit a screenshot of the code and the corresponding output.
For questions 7 to 10, create another csv file containing list of most successful players in the game of your choice with data as: {Name, Tournament, City, Country, Sport, World_Ranking}
Q7. Read this csv using Pandas and save it into a DataFrame called df_2. Submit a screenshot of the code and the corresponding output.
Q8. Combine the two DataFrames (df_1) and (df_2) on World_Ranking attribute. Submit a screenshot of the code and the corresponding output.
Q9. To the merged DataFrame, add a prefix & suffix to the columns of your choice. Submit a screenshot of the code and the corresponding output.
Q10. Generate the statistical summary of all the numerical features of the combined DataFrame. Submit a screenshot of the code and the corresponding output.
PART 2 - Application Development
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Using the Movie Recommendation System starter kit, build a Recommender System of your choice. For example, a course recommender system for an EdTech platform, a music recommender system for a music app, a product recommender system for an e-commerce platform etc. Submit the kandi kit link of the customized recommender system your team has built the Challenge Submission Form.
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The starter kit provides Movie Recommendation to users using Pandas library and applying the concept of collaborative filtering. CLICK HERE to watch a 5 min tutorial on how to use the Movie Recommendation System starter kit.
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You can customize this solution by feeding your own data set to the existing code for your expected solution/result and then creating a kandi kit for submission.
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Before you start making the submission kandi kit, ensure you have completed your solution, and your solution repository is uploaded to GitHub. If you are not aware of how to add your work to GitHub, please refer to this link - Creating a new repository - GitHub Docs.
CLICK HERE to watch a 5 min video on how to create and submit your kandi kit!
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Challenge Submission Form: When you are ready, CLICK HERE to submit your responses.
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Submission Deadline: 10 pm on Sunday, 12th February 2023.
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Judging Criteria: All submissions will be judged and recognized based on the following.
PART 1 - Coding Exercises:
(1) No. of coding exercises completed
(2) Working code and the corresponding output for each question (as submitted in the screenshot for each question)
PART 2 - Application Development:
(1) Technical modifications and customization made to the starter kit provided
(2) Quality of the solution/kandi kit submitted
Submission is mandatory to complete the challenge and get your certificate!
We are here for you all through this challenge!
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Use kandi as a resource to support you with the coding exercises and ML application development!
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PART 1 - Coding Exercises: CLICK HERE to watch a 5 min video on on how to search for code snippets and complete the coding exercises.
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PART 2 - Application Development: CLICK HERE to watch a 5 min video on how to create and submit your customized recommender solution kandi kit.
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For further support with this challenge, you may connect with us via the chat feature , or reply to the thread here below. You must sign up to be able to use these features. So sign up and reach out to receive real-time support all through this challenge!
- Results of the Build Mania Challenge will be announced via an online session. You will receive the dial-in details of the Awards Ceremony via email once the challenge closes.
- All participants will receive a certificate and badge by 15th February!
