Indian Candidates for General Election 2019

世界上最大的民主国家有超过6亿选民为543个选区的8500多名候选人投票，这是潜在的数据金矿。尽管存在关于每个候选人获得的选票和每个候选人的个人信息的单独数据集，但没有包含这些信息的综合数据集。因此，与该域中的大多数现有数据集相比，该数据集将提供更多的可用性。可在此数据集上执行2个主要任务：探索性数据分析，以可视化候选人的每个功能的影响，以及使用机器学习来预测候选人获胜的机会。

The world's largest democracy hosts an election where over 600 million voters cast ballots for more than 8,500 candidates across 543 constituencies, making this a potential data goldmine. While separate datasets exist for the votes received by each candidate and the personal information of individual candidates, no integrated dataset combining both types of information is currently available. As such, this dataset will offer greater usability compared to most existing datasets in this domain. Two primary tasks can be performed on this dataset: Exploratory Data Analysis (EDA) to visualize the impact of each feature of the candidates, and machine learning-based prediction of candidates' winning chances.

搜集汇总

背景与挑战

背景概述

该数据集整合了2019年印度大选中8500多名候选人的选票和个人信息，覆盖543个选区，数据来源于MyNeta.info和印度选举委员会网站。它适用于探索性数据分析和机器学习预测任务，相比现有数据集具有更高的可用性。