Enroll Course: https://www.udemy.com/course/rohitbasistgurjar-data-analysis-project-on-electoral-bond/
The world of political finance can often feel opaque, but thanks to a recent Udemy course, “Data Analysis Project on Electoral Bond in Python Colab,” I’ve gained a much clearer understanding of the Electoral Bond data released by the SBI to the Election Commission of India. This comprehensive project walks you through analyzing data spanning from April 2019 to January 2024, covering both purchase and redemption details.
The course meticulously guides you through the data, starting with a thorough overview. It highlights a crucial finding: no Electoral Bond was redeemed more than 15 days after its purchase, suggesting a relatively swift financial cycle. A significant portion of the project is dedicated to data merging and validation, a critical step in any data analysis. The instructor effectively demonstrates how to create a unique identifier by merging ‘Prefix’ and ‘Bond Number’ columns. The discrepancies found – 1,680 unmatched purchase entries and 130 unmatched redemption entries – underscore the importance of this validation process. Furthermore, the course emphasizes standardizing data types and cleaning naming inconsistencies, essential for reliable analysis.
One of the most illuminating aspects of this course is the identification of top purchasers. The project clearly outlines the top 5 entities that bought the most bonds between 2019 and 2024: Future Gaming and Hotel Services, Megha Engineering and Infrastructure, Qwik Supply Chain Private Limited, Haldi Energy, and Vedanta Limited. The insights into denominations are equally striking, with bonds of ₹1 crore denomination proving to be the most prevalent across all donations.
Time-based trends are also thoroughly explored. The course identifies peak purchase months as January, April, and October, with 2022 and 2023 standing out as peak years for bond purchases. The redemption patterns are also analyzed, revealing that the majority of bonds are redeemed within 5 days of purchase.
Finally, the course delves into political party encashments, ranking the top parties by the amount of money received through Electoral Bonds: the Bharatiya Janata Party (BJP), Trinamool Congress, and Indian National Congress. The project concludes with practical data exploration techniques, including adding new columns for day names, months, and years, and utilizing crosstab analysis to visualize purchase trends against political party denomination sums.
For anyone interested in the intersection of finance, politics, and data, this course is a highly recommended practical guide. It’s an excellent hands-on experience that equips you with the skills to tackle real-world datasets using Python in Google Colab.
Enroll Course: https://www.udemy.com/course/rohitbasistgurjar-data-analysis-project-on-electoral-bond/