===Profile Information
**Name:** Nivas Ramisetty
**IRC nickname on libera.chat IRC (optional):** Nivas10798
**We**Github Profile**:** https://github.com/Nivas10798/
**Resume (optional)****Linkedin Profile:** https://www.linkedin.com/in/nivas10798/
**Location (country or state):** Andhra Pradesh, India
**Typical working hours (include your timezone):** 9 am to 12 pm and 5 pm to 12 am (UTC+05:30)
===Synopsis
//**Short summary describing your project and how it will benefit Wikimedia projects**//
**Project document:** https://phabricator.wikimedia.org/T304826
Campaigns are content/theme focused activities organized annually by collaborating with many volunteer communities and other government/private institutions. A hidden advantage of campaigns is, it acts as an open door to the Wikimedia world for new participants who are either interested or working in the field of the campaign theme thus improving the content and communities experiences. Therefore, a dashboard can give a better understanding of the retention of new users on various Wikimedia projects over different time periods after a campaign has ended.
**Possible Mentor(s):** **@KCVelaga**, **@Jayprakash12345**, **@Sadads**
- Have you contacted your mentors already?**Possible Mentor(s):** **@KCVelaga**, **@Jayprakash12345**, **@Sadads**
-- Yes,**Have you contacted @Jayprakash12345, and @KCVelaga for micro-task submissions.your mentors already?**
- Yes, contacted @Jayprakash12345, and @KCVelaga(for micro-task submissions).
===Deliverables
Following are the deliverables of the project:
- A dashboard tool to track the edits of new users who registered their accounts during a selected campaign, over different time intervals after the end of the campaign.
- Weekly report of works done and progress of the project.
- Final project documentation describing the working of the tool.
===Timeline
| **Period** | **Task** |
|May 20 to June 12 | Community bonding period. Contributors to interact with project mentors and MediaWiki developers for guidance, discuss the outcomes related to the project and refine the project proposal (if needed). Learn Flask/Django and big data tools like Spark/Hive.
|June 13 to June 19 | Consult mentors, discuss building ETL pipelines and necessary data to create visualizations
|June 20 to June 26 | Build SQL query to extract necessary data from the databases for the selected campaign
|June 27 to July 10 | Check the dataset extracted from databases with project mentors. Start creating visualizations from the dataset. Finish visualizations and improve them by taking feedback from mentors
|July 11 to July 24 | Work on the building a prototype dashboard using web apps like Streamlit/Dash and present the prototype to the mentors
|July 25 to July 29 | **Phase 1 evaluation**
|July 25 to July 31| List out the necessary improvements for UI from mentors' feedback on the prototype and include them in the final dashboard created using HTML/CSS and Flask/Django
|August 1 to August 7 | Developing the frontend using HTML, CSS and backend using Flask/Django framework
|August 8 to August 14 | Integrate the backend with the frontend, check for bugs and fix them
|August 15 to August 21 | Display a demo to the mentors and take feedback for improvements
|August 22 to August 28 | Make improvements and test the final product
|August 29 to September 4 | Finish the final project documentation
|September 5 to September 11 | **Project submission and final evaluation**
|September 12 to September 19 | Mentors submit final evaluations of the contributor
|September 20 | **Announcement of GSoC 2022 results**
===Participation
Describe how you plan to communicate progress and ask for helpuring the development of the project,
- I will be using Zulip as my primary communication platform to interact and discuss my doubts, where you plan to publish your source code, etcdevelopments and progress of the project.
- I will be submitting weekly updates regarding the project over Zulip or any other platform depending on the mentors' comfort.
- I will be having a bi-weekly call with one/all the mentors to discuss my thoughts on development and show the progress achieved till then.
- I will be using Github or other open repositories as suggested by the mentors to publish my project code.
===About Me
- **Your education:** I finished my bachelor's in 2020 and currently pursuing a post-graduation program in Data Science.
- **How did you hear about this program?** A friend of mine has applied for previous iterations of GSoC and suggested me to apply.
- **Will you have any other time commitments, such as school work, another job, planned vacation, etc, during the duration of the program?**
-- Currently, my course is on pause and will resume in the month of August. Since it is a part-time course, I will be able to work on the project even if the course resumes.
- **We advise all candidates eligible for Google Summer of Code and Outreachy to apply for both programs. Are you planning to apply to both programs and, if so, with what organization(s)?**
-- No, I am applying for Google Summer of Code only.
- **What does making this project happen mean to you?**
-- I consider contributing to this project as a once in a lifetime opportunity as campaigns retention stats are very essential in any organisation's development. I view the development of this tool as a beginning milestone for the creation of many other tools related to user retention. I firmly believe that my data science skills can help the organization get the best output for the project besides allowing me to pursue a career in my field of interest.
===Past Experience
- I have experience in building web apps using Streamlit.
-- FIFA player rating prediction: https://fifa-20-data-analysis.herokuapp.com/
- I am familiar with data visualization libraries like Matplotlib, Seaborn, Bokeh, and Plotly and other libraries useful for data analysis like Pandas, and NumPy.
-- car selling price prediction: https://github.com/Nivas10798/car-selling-price-prediction
- Microtasks
-- Completed the Micro-tasks - T304974 , T305309 .
===Any Other Info
Add any other relevant information such as UI mockups, references to related projects, a link to your proof of concept code, etc