Data Dictionary

Column Type Label Description
id numeric index
month text Month
state_name text State
state_code text State Code
district_name text District
district_code text District Code
assembly_no text Number of assembly election
ac_name text Name of constituency
ac_no text Constituency number
ac_type text Type of constitutency
candidate_name text Name of candidate
sex text Gender of candidate
age numeric Age of candidate
candidate_type text Type of candidate
party text Name of party
position numeric Position secured in election
ac_total_candidates numeric Total number of candidates participated in elections
total_electors numeric Total number of electors
total_votes numeric Number of votes polled during the elections for the candidate
total_valid_votes numeric Number of valid votes polled during the elections for the candidate
vote_share_percentage numeric Percentage vote share by candidate
margin numeric Difference in votes between a candidate next in position
margin_percentage numeric percentage of margin with candidate next in position
turnout_percentage numeric Percentage turnout in constituency
poll_no numeric If the election is bye-election or not.
delimit_id numeric Delimitation Number

Additional Information

Field Value
Data last updated May 11, 2023
Metadata last updated May 11, 2023
Created May 11, 2023
Format CSV
License Open Data Commons Attribution License
Additional infonan
Data insightsThe Himachal Assembly Elections dataset provides valuable insights into the electoral process and candidate dynamics. Here are some questions that can be explored using the dataset: Candidate Profile Analysis: What is the distribution of candidates based on gender? How does the age distribution of candidates vary across different parties? Are there any correlations between educational qualifications and candidate success? Party Performance and Alliances: Which political party fielded the maximum number of candidates in the elections? Did any parties form pre-election alliances? If so, how did it impact their performance? How does the vote share of major parties compare across different constituencies? Constituency-Level Analysis: Which constituencies had the highest voter turnout in the elections? Were there any constituencies with a significant swing in voting patterns compared to previous elections? How did reserved constituencies perform in terms of candidate diversity and representation? Election Results and Trends: Who were the top-performing candidates in terms of votes received? Did any independent candidates emerge as winners in the elections? Are there any noticeable trends or patterns in the election results across different election cycles? Voter Behavior and Participation: How does the voter turnout vary across different demographics, such as age groups or gender? Are there any noticeable differences in voting patterns between rural and urban constituencies? Did any constituencies witness a significant increase or decrease in voter participation compared to previous elections? Exploring these questions using the Himachal Assembly Elections dataset can provide valuable insights into the electoral landscape, candidate profiles, party dynamics, and voter behavior in Himachal.
Data last updated2,023
Data retreival date2023-04-26 00:00:00
Datastore activeTrue
District no12
FrequencyElection
GranularityAssembly Constituency
Has viewsTrue
Idaa74d1cf-aaf8-4a75-a2db-282968a40bb6
Mimetypetext/csv
No indicators12
Package id7771573f-41b4-40be-b96a-dd0aaba71494
Position0
Size187.6 KiB
Stateactive
States uts no1
Tehsil nonan
Url typeupload
Years covered2009-2023
Methodology
Similar Resources
Granularity Level Assembly Constituency
Data Extraction Page
Data Retreival Date 2023-04-26 00:00:00
Data Last Updated 2023
Sku
Dataset Frequency Election
Years Covered 2009-2023
No of States/UT(s) 1
No of Districts 12
No of Tehsils/blocks nan
No of Gram Panchayats
Additional Information nan
Number of Indicators 12
Insights from the dataset The Himachal Assembly Elections dataset provides valuable insights into the electoral process and candidate dynamics. Here are some questions that can be explored using the dataset: Candidate Profile Analysis: What is the distribution of candidates based on gender? How does the age distribution of candidates vary across different parties? Are there any correlations between educational qualifications and candidate success? Party Performance and Alliances: Which political party fielded the maximum number of candidates in the elections? Did any parties form pre-election alliances? If so, how did it impact their performance? How does the vote share of major parties compare across different constituencies? Constituency-Level Analysis: Which constituencies had the highest voter turnout in the elections? Were there any constituencies with a significant swing in voting patterns compared to previous elections? How did reserved constituencies perform in terms of candidate diversity and representation? Election Results and Trends: Who were the top-performing candidates in terms of votes received? Did any independent candidates emerge as winners in the elections? Are there any noticeable trends or patterns in the election results across different election cycles? Voter Behavior and Participation: How does the voter turnout vary across different demographics, such as age groups or gender? Are there any noticeable differences in voting patterns between rural and urban constituencies? Did any constituencies witness a significant increase or decrease in voter participation compared to previous elections? Exploring these questions using the Himachal Assembly Elections dataset can provide valuable insights into the electoral landscape, candidate profiles, party dynamics, and voter behavior in Himachal.
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