Changes
On December 19, 2025, 8:07:55 AM UTC,
-
Added field
geo_columns
with value['state_code', 'district_code']
to resource Census PCA Demography - Districts in Census PCA Demography
| f | 1 | { | f | 1 | { |
| 2 | "SDGs": [], | 2 | "SDGs": [], | ||
| 3 | "author": null, | 3 | "author": null, | ||
| 4 | "author_email": null, | 4 | "author_email": null, | ||
| 5 | "creator_user_id": "2d6f4b88-ac2a-4d68-8d0f-7c6235b7b442", | 5 | "creator_user_id": "2d6f4b88-ac2a-4d68-8d0f-7c6235b7b442", | ||
| 6 | "extras": [ | 6 | "extras": [ | ||
| 7 | { | 7 | { | ||
| 8 | "key": "fields", | 8 | "key": "fields", | ||
| 9 | "value": "id, year, state_name, state_code, rural_urban, level, | 9 | "value": "id, year, state_name, state_code, rural_urban, level, | ||
| 10 | gender, age, social_group, literacy, working_status, worker_type, | 10 | gender, age, social_group, literacy, working_status, worker_type, | ||
| 11 | occupation, population, id, year, state_name, state_code, | 11 | occupation, population, id, year, state_name, state_code, | ||
| 12 | district_name, district_code, rural_urban, level, gender, age, | 12 | district_name, district_code, rural_urban, level, gender, age, | ||
| 13 | social_group, literacy, working_status, worker_type, occupation, | 13 | social_group, literacy, working_status, worker_type, occupation, | ||
| 14 | population, id, year, state_name, state_code, district_name, | 14 | population, id, year, state_name, state_code, district_name, | ||
| 15 | district_code, sub_district_name, sub_district_code, block_name, | 15 | district_code, sub_district_name, sub_district_code, block_name, | ||
| 16 | block_code, rural_urban, level, gender, age, social_group, literacy, | 16 | block_code, rural_urban, level, gender, age, social_group, literacy, | ||
| 17 | working_status, worker_type, occupation, population, id, year, | 17 | working_status, worker_type, occupation, population, id, year, | ||
| 18 | state_name, state_code, district_name, district_code, | 18 | state_name, state_code, district_name, district_code, | ||
| 19 | subdistrict_name, subdistrict_code, rural_urban, level, gender, age, | 19 | subdistrict_name, subdistrict_code, rural_urban, level, gender, age, | ||
| 20 | social_group, literacy, working_status, worker_type, occupation, | 20 | social_group, literacy, working_status, worker_type, occupation, | ||
| 21 | population" | 21 | population" | ||
| 22 | } | 22 | } | ||
| 23 | ], | 23 | ], | ||
| 24 | "groups": [], | 24 | "groups": [], | ||
| 25 | "id": "2a41af7b-7922-4d8f-83c9-d5ebcb8a5f54", | 25 | "id": "2a41af7b-7922-4d8f-83c9-d5ebcb8a5f54", | ||
| 26 | "isopen": false, | 26 | "isopen": false, | ||
| 27 | "license_id": "", | 27 | "license_id": "", | ||
| 28 | "license_title": "", | 28 | "license_title": "", | ||
| 29 | "maintainer": null, | 29 | "maintainer": null, | ||
| 30 | "maintainer_email": null, | 30 | "maintainer_email": null, | ||
| 31 | "metadata_created": "2023-10-16T07:31:32.246939", | 31 | "metadata_created": "2023-10-16T07:31:32.246939", | ||
| n | 32 | "metadata_modified": "2025-12-19T08:07:53.641886", | n | 32 | "metadata_modified": "2025-12-19T08:07:54.895447", |
| 33 | "methodology": "", | 33 | "methodology": "", | ||
| 34 | "name": "census-pca-demography", | 34 | "name": "census-pca-demography", | ||
| 35 | "notes": "", | 35 | "notes": "", | ||
| 36 | "num_resources": 4, | 36 | "num_resources": 4, | ||
| 37 | "num_tags": 1, | 37 | "num_tags": 1, | ||
| 38 | "organization": { | 38 | "organization": { | ||
| 39 | "approval_status": "approved", | 39 | "approval_status": "approved", | ||
| 40 | "created": "2022-12-05T03:44:54.080358", | 40 | "created": "2022-12-05T03:44:54.080358", | ||
| 41 | "description": "", | 41 | "description": "", | ||
| 42 | "id": "94317457-d297-4549-9640-7865034682c5", | 42 | "id": "94317457-d297-4549-9640-7865034682c5", | ||
| 43 | "image_url": "2023-12-08-070530.691105iSB-IDP-Logo.png", | 43 | "image_url": "2023-12-08-070530.691105iSB-IDP-Logo.png", | ||
| 44 | "is_organization": true, | 44 | "is_organization": true, | ||
| 45 | "name": "idp-organization", | 45 | "name": "idp-organization", | ||
| 46 | "state": "active", | 46 | "state": "active", | ||
| 47 | "title": "IDP organization", | 47 | "title": "IDP organization", | ||
| 48 | "type": "organization" | 48 | "type": "organization" | ||
| 49 | }, | 49 | }, | ||
| 50 | "owner_org": "94317457-d297-4549-9640-7865034682c5", | 50 | "owner_org": "94317457-d297-4549-9640-7865034682c5", | ||
| 51 | "private": false, | 51 | "private": false, | ||
| 52 | "relationships_as_object": [], | 52 | "relationships_as_object": [], | ||
| 53 | "relationships_as_subject": [], | 53 | "relationships_as_subject": [], | ||
| 54 | "resources": [ | 54 | "resources": [ | ||
| 55 | { | 55 | { | ||
| 56 | "additional_info": "", | 56 | "additional_info": "", | ||
| 57 | "cache_last_updated": null, | 57 | "cache_last_updated": null, | ||
| 58 | "cache_url": null, | 58 | "cache_url": null, | ||
| 59 | "created": "2023-10-16T09:26:08.335721", | 59 | "created": "2023-10-16T09:26:08.335721", | ||
| 60 | "data_dict": { | 60 | "data_dict": { | ||
| 61 | "additional_info": "", | 61 | "additional_info": "", | ||
| 62 | "cache_last_updated": null, | 62 | "cache_last_updated": null, | ||
| 63 | "cache_url": null, | 63 | "cache_url": null, | ||
| 64 | "created": "2023-10-16T09:26:08.335721", | 64 | "created": "2023-10-16T09:26:08.335721", | ||
| 65 | "data_extraction_page": "B-01: Main workers, marginal workers, | 65 | "data_extraction_page": "B-01: Main workers, marginal workers, | ||
| 66 | non-workers and those marginal workers, non-workers seeking/available | 66 | non-workers and those marginal workers, non-workers seeking/available | ||
| 67 | for work classified by age and sex", | 67 | for work classified by age and sex", | ||
| 68 | "data_insights": "Data Insights that can be drawn:Demographic | 68 | "data_insights": "Data Insights that can be drawn:Demographic | ||
| 69 | Distribution: Analyze the distribution of the population across | 69 | Distribution: Analyze the distribution of the population across | ||
| 70 | states, rural vs. urban areas, and different age groups.Gender | 70 | states, rural vs. urban areas, and different age groups.Gender | ||
| 71 | Disparity: Evaluate differences in working status, occupation, and | 71 | Disparity: Evaluate differences in working status, occupation, and | ||
| 72 | literacy based on gender.Employment Overview: Understand the | 72 | literacy based on gender.Employment Overview: Understand the | ||
| 73 | distribution of main workers, marginal workers, non-workers, and those | 73 | distribution of main workers, marginal workers, non-workers, and those | ||
| 74 | seeking jobs, allowing policymakers to assess employment and | 74 | seeking jobs, allowing policymakers to assess employment and | ||
| 75 | unemployment rates.Occupational Analysis: Gain insights into popular | 75 | unemployment rates.Occupational Analysis: Gain insights into popular | ||
| 76 | occupations across different states and decipher trends across rural | 76 | occupations across different states and decipher trends across rural | ||
| 77 | and urban landscapes.Literacy and Employment: Investigate the | 77 | and urban landscapes.Literacy and Employment: Investigate the | ||
| 78 | relationship between literacy levels and working status or | 78 | relationship between literacy levels and working status or | ||
| 79 | occupation.Social Group Dynamics: Analyze employment, literacy, and | 79 | occupation.Social Group Dynamics: Analyze employment, literacy, and | ||
| 80 | demographic trends across different social groups.", | 80 | demographic trends across different social groups.", | ||
| 81 | "data_last_updated": "2011", | 81 | "data_last_updated": "2011", | ||
| 82 | "data_retreival_date": "6/23/2022", | 82 | "data_retreival_date": "6/23/2022", | ||
| 83 | "datastore_active": true, | 83 | "datastore_active": true, | ||
| 84 | "description": "The \"Census PCA Demography - States\" dataset | 84 | "description": "The \"Census PCA Demography - States\" dataset | ||
| 85 | provides comprehensive details regarding the working status, | 85 | provides comprehensive details regarding the working status, | ||
| 86 | occupation, and demographic characteristics of the Indian population, | 86 | occupation, and demographic characteristics of the Indian population, | ||
| 87 | based on state-wise data sourced from the official Indian Census | 87 | based on state-wise data sourced from the official Indian Census | ||
| 88 | website. The dataset showcases a combination of both categorical and | 88 | website. The dataset showcases a combination of both categorical and | ||
| 89 | numeric data, shedding light on the distribution of main workers, | 89 | numeric data, shedding light on the distribution of main workers, | ||
| 90 | marginal workers, non-workers, and those seeking/available for work | 90 | marginal workers, non-workers, and those seeking/available for work | ||
| 91 | across various parameters such as age, gender, literacy, and social | 91 | across various parameters such as age, gender, literacy, and social | ||
| 92 | groupings. Additionally, this dataset distinguishes its records based | 92 | groupings. Additionally, this dataset distinguishes its records based | ||
| 93 | on rural or urban settings.", | 93 | on rural or urban settings.", | ||
| 94 | "district_no": "", | 94 | "district_no": "", | ||
| 95 | "format": "CSV", | 95 | "format": "CSV", | ||
| 96 | "frequency": "Decadal", | 96 | "frequency": "Decadal", | ||
| 97 | "gp_no": "", | 97 | "gp_no": "", | ||
| 98 | "granularity": "State", | 98 | "granularity": "State", | ||
| 99 | "hash": "", | 99 | "hash": "", | ||
| 100 | "id": "ed2203bf-e493-4b6a-a0ab-d343d4369687", | 100 | "id": "ed2203bf-e493-4b6a-a0ab-d343d4369687", | ||
| 101 | "idp_ready": true, | 101 | "idp_ready": true, | ||
| 102 | "last_modified": "2023-10-16T09:26:08.305475", | 102 | "last_modified": "2023-10-16T09:26:08.305475", | ||
| 103 | "lgd_mapping": "yes", | 103 | "lgd_mapping": "yes", | ||
| 104 | "metadata_modified": "2024-08-22T10:11:01.791465", | 104 | "metadata_modified": "2024-08-22T10:11:01.791465", | ||
| 105 | "methodology": "The data is sourced directly from the official | 105 | "methodology": "The data is sourced directly from the official | ||
| 106 | Census India website. The Census of India follows a decennial pattern, | 106 | Census India website. The Census of India follows a decennial pattern, | ||
| 107 | collecting detailed demographic and occupational data from households | 107 | collecting detailed demographic and occupational data from households | ||
| 108 | across different states. Enumerators are trained and employed to | 108 | across different states. Enumerators are trained and employed to | ||
| 109 | gather this data, ensuring accuracy and comprehensive coverage. Once | 109 | gather this data, ensuring accuracy and comprehensive coverage. Once | ||
| 110 | the raw data is obtained, it's processed and classified into | 110 | the raw data is obtained, it's processed and classified into | ||
| 111 | categories like main workers, marginal workers, etc., before being | 111 | categories like main workers, marginal workers, etc., before being | ||
| 112 | made available to the public.", | 112 | made available to the public.", | ||
| 113 | "mimetype": null, | 113 | "mimetype": null, | ||
| 114 | "mimetype_inner": null, | 114 | "mimetype_inner": null, | ||
| 115 | "name": "Census PCA Demography - States", | 115 | "name": "Census PCA Demography - States", | ||
| 116 | "no_indicators": "1", | 116 | "no_indicators": "1", | ||
| 117 | "package_id": "2a41af7b-7922-4d8f-83c9-d5ebcb8a5f54", | 117 | "package_id": "2a41af7b-7922-4d8f-83c9-d5ebcb8a5f54", | ||
| 118 | "position": 0, | 118 | "position": 0, | ||
| 119 | "resource_type": null, | 119 | "resource_type": null, | ||
| 120 | "similar_resources": "", | 120 | "similar_resources": "", | ||
| 121 | "size": 1084390, | 121 | "size": 1084390, | ||
| 122 | "sku": "moha-census_pca_demography-st-dc-abc", | 122 | "sku": "moha-census_pca_demography-st-dc-abc", | ||
| 123 | "state": "active", | 123 | "state": "active", | ||
| 124 | "states_uts_no": "36", | 124 | "states_uts_no": "36", | ||
| 125 | "tehsil_no": "", | 125 | "tehsil_no": "", | ||
| 126 | "url": | 126 | "url": | ||
| 127 | 493-4b6a-a0ab-d343d4369687/download/census-pca-demography-states.csv", | 127 | 493-4b6a-a0ab-d343d4369687/download/census-pca-demography-states.csv", | ||
| 128 | "url_type": "upload", | 128 | "url_type": "upload", | ||
| 129 | "years_covered": "2011.0" | 129 | "years_covered": "2011.0" | ||
| 130 | }, | 130 | }, | ||
| 131 | "data_extraction_page": "B-01: Main workers, marginal workers, | 131 | "data_extraction_page": "B-01: Main workers, marginal workers, | ||
| 132 | non-workers and those marginal workers, non-workers seeking/available | 132 | non-workers and those marginal workers, non-workers seeking/available | ||
| 133 | for work classified by age and sex", | 133 | for work classified by age and sex", | ||
| 134 | "data_insights": "Data Insights that can be drawn:Demographic | 134 | "data_insights": "Data Insights that can be drawn:Demographic | ||
| 135 | Distribution: Analyze the distribution of the population across | 135 | Distribution: Analyze the distribution of the population across | ||
| 136 | states, rural vs. urban areas, and different age groups.Gender | 136 | states, rural vs. urban areas, and different age groups.Gender | ||
| 137 | Disparity: Evaluate differences in working status, occupation, and | 137 | Disparity: Evaluate differences in working status, occupation, and | ||
| 138 | literacy based on gender.Employment Overview: Understand the | 138 | literacy based on gender.Employment Overview: Understand the | ||
| 139 | distribution of main workers, marginal workers, non-workers, and those | 139 | distribution of main workers, marginal workers, non-workers, and those | ||
| 140 | seeking jobs, allowing policymakers to assess employment and | 140 | seeking jobs, allowing policymakers to assess employment and | ||
| 141 | unemployment rates.Occupational Analysis: Gain insights into popular | 141 | unemployment rates.Occupational Analysis: Gain insights into popular | ||
| 142 | occupations across different states and decipher trends across rural | 142 | occupations across different states and decipher trends across rural | ||
| 143 | and urban landscapes.Literacy and Employment: Investigate the | 143 | and urban landscapes.Literacy and Employment: Investigate the | ||
| 144 | relationship between literacy levels and working status or | 144 | relationship between literacy levels and working status or | ||
| 145 | occupation.Social Group Dynamics: Analyze employment, literacy, and | 145 | occupation.Social Group Dynamics: Analyze employment, literacy, and | ||
| 146 | demographic trends across different social groups.", | 146 | demographic trends across different social groups.", | ||
| 147 | "data_last_updated": "2011", | 147 | "data_last_updated": "2011", | ||
| 148 | "data_retreival_date": "6/23/2022", | 148 | "data_retreival_date": "6/23/2022", | ||
| 149 | "datastore_active": true, | 149 | "datastore_active": true, | ||
| 150 | "description": "The \"Census PCA Demography - States\" dataset | 150 | "description": "The \"Census PCA Demography - States\" dataset | ||
| 151 | provides comprehensive details regarding the working status, | 151 | provides comprehensive details regarding the working status, | ||
| 152 | occupation, and demographic characteristics of the Indian population, | 152 | occupation, and demographic characteristics of the Indian population, | ||
| 153 | based on state-wise data sourced from the official Indian Census | 153 | based on state-wise data sourced from the official Indian Census | ||
| 154 | website. The dataset showcases a combination of both categorical and | 154 | website. The dataset showcases a combination of both categorical and | ||
| 155 | numeric data, shedding light on the distribution of main workers, | 155 | numeric data, shedding light on the distribution of main workers, | ||
| 156 | marginal workers, non-workers, and those seeking/available for work | 156 | marginal workers, non-workers, and those seeking/available for work | ||
| 157 | across various parameters such as age, gender, literacy, and social | 157 | across various parameters such as age, gender, literacy, and social | ||
| 158 | groupings. Additionally, this dataset distinguishes its records based | 158 | groupings. Additionally, this dataset distinguishes its records based | ||
| 159 | on rural or urban settings.", | 159 | on rural or urban settings.", | ||
| 160 | "district_no": "", | 160 | "district_no": "", | ||
| 161 | "format": "CSV", | 161 | "format": "CSV", | ||
| 162 | "frequency": "Decadal", | 162 | "frequency": "Decadal", | ||
| 163 | "geo_columns": [ | 163 | "geo_columns": [ | ||
| 164 | "state_code" | 164 | "state_code" | ||
| 165 | ], | 165 | ], | ||
| 166 | "gp_no": "", | 166 | "gp_no": "", | ||
| 167 | "granularity": "State", | 167 | "granularity": "State", | ||
| 168 | "hash": "", | 168 | "hash": "", | ||
| 169 | "id": "ed2203bf-e493-4b6a-a0ab-d343d4369687", | 169 | "id": "ed2203bf-e493-4b6a-a0ab-d343d4369687", | ||
| 170 | "idp_ready": true, | 170 | "idp_ready": true, | ||
| 171 | "last_modified": "2023-10-16T09:26:08.305475", | 171 | "last_modified": "2023-10-16T09:26:08.305475", | ||
| 172 | "lgd_mapping": "yes", | 172 | "lgd_mapping": "yes", | ||
| 173 | "metadata_modified": "2025-12-19T08:07:53.646821", | 173 | "metadata_modified": "2025-12-19T08:07:53.646821", | ||
| 174 | "methodology": "The data is sourced directly from the official | 174 | "methodology": "The data is sourced directly from the official | ||
| 175 | Census India website. The Census of India follows a decennial pattern, | 175 | Census India website. The Census of India follows a decennial pattern, | ||
| 176 | collecting detailed demographic and occupational data from households | 176 | collecting detailed demographic and occupational data from households | ||
| 177 | across different states. Enumerators are trained and employed to | 177 | across different states. Enumerators are trained and employed to | ||
| 178 | gather this data, ensuring accuracy and comprehensive coverage. Once | 178 | gather this data, ensuring accuracy and comprehensive coverage. Once | ||
| 179 | the raw data is obtained, it's processed and classified into | 179 | the raw data is obtained, it's processed and classified into | ||
| 180 | categories like main workers, marginal workers, etc., before being | 180 | categories like main workers, marginal workers, etc., before being | ||
| 181 | made available to the public.", | 181 | made available to the public.", | ||
| 182 | "mimetype": null, | 182 | "mimetype": null, | ||
| 183 | "mimetype_inner": null, | 183 | "mimetype_inner": null, | ||
| 184 | "name": "Census PCA Demography - States", | 184 | "name": "Census PCA Demography - States", | ||
| 185 | "no_indicators": "1", | 185 | "no_indicators": "1", | ||
| 186 | "package_id": "2a41af7b-7922-4d8f-83c9-d5ebcb8a5f54", | 186 | "package_id": "2a41af7b-7922-4d8f-83c9-d5ebcb8a5f54", | ||
| 187 | "position": 0, | 187 | "position": 0, | ||
| 188 | "resource_type": null, | 188 | "resource_type": null, | ||
| 189 | "similar_resources": "", | 189 | "similar_resources": "", | ||
| 190 | "size": 1084390, | 190 | "size": 1084390, | ||
| 191 | "sku": "moha-census_pca_demography-st-dc-abc", | 191 | "sku": "moha-census_pca_demography-st-dc-abc", | ||
| 192 | "state": "active", | 192 | "state": "active", | ||
| 193 | "states_uts_no": "36", | 193 | "states_uts_no": "36", | ||
| 194 | "tehsil_no": "", | 194 | "tehsil_no": "", | ||
| 195 | "url": | 195 | "url": | ||
| 196 | 493-4b6a-a0ab-d343d4369687/download/census-pca-demography-states.csv", | 196 | 493-4b6a-a0ab-d343d4369687/download/census-pca-demography-states.csv", | ||
| 197 | "url_type": "upload", | 197 | "url_type": "upload", | ||
| 198 | "years_covered": "2011.0" | 198 | "years_covered": "2011.0" | ||
| 199 | }, | 199 | }, | ||
| 200 | { | 200 | { | ||
| 201 | "additional_info": "", | 201 | "additional_info": "", | ||
| 202 | "cache_last_updated": null, | 202 | "cache_last_updated": null, | ||
| 203 | "cache_url": null, | 203 | "cache_url": null, | ||
| 204 | "created": "2023-10-16T09:35:04.861039", | 204 | "created": "2023-10-16T09:35:04.861039", | ||
| 205 | "data_extraction_page": "B-01: Main workers, marginal workers, | 205 | "data_extraction_page": "B-01: Main workers, marginal workers, | ||
| 206 | non-workers and those marginal workers, non-workers seeking/available | 206 | non-workers and those marginal workers, non-workers seeking/available | ||
| 207 | for work classified by age and sex", | 207 | for work classified by age and sex", | ||
| 208 | "data_insights": "Data Insights that can be drawn:Regional | 208 | "data_insights": "Data Insights that can be drawn:Regional | ||
| 209 | Differences: By examining the data across different states and | 209 | Differences: By examining the data across different states and | ||
| 210 | districts, one can discern patterns related to employment and | 210 | districts, one can discern patterns related to employment and | ||
| 211 | demographics, possibly highlighting more prosperous regions versus | 211 | demographics, possibly highlighting more prosperous regions versus | ||
| 212 | those requiring more developmental attention.Gender Dynamics: The | 212 | those requiring more developmental attention.Gender Dynamics: The | ||
| 213 | dataset classifies information by gender, enabling insights into | 213 | dataset classifies information by gender, enabling insights into | ||
| 214 | gender disparities in employment, literacy, and other socio-economic | 214 | gender disparities in employment, literacy, and other socio-economic | ||
| 215 | factors.Literacy & Employment: The relationship between literacy | 215 | factors.Literacy & Employment: The relationship between literacy | ||
| 216 | levels and types of occupation or employment status can be | 216 | levels and types of occupation or employment status can be | ||
| 217 | explored.Social Group Insights: The categorization by social group | 217 | explored.Social Group Insights: The categorization by social group | ||
| 218 | might shed light on societal structures, possibly indicating which | 218 | might shed light on societal structures, possibly indicating which | ||
| 219 | groups might be more marginalized in terms of employment and | 219 | groups might be more marginalized in terms of employment and | ||
| 220 | educational opportunities.Age Dynamics: The classification by age can | 220 | educational opportunities.Age Dynamics: The classification by age can | ||
| 221 | be used to understand the age structure of workers in different | 221 | be used to understand the age structure of workers in different | ||
| 222 | occupations, providing insights into youth employment, elderly | 222 | occupations, providing insights into youth employment, elderly | ||
| 223 | participation, and more.", | 223 | participation, and more.", | ||
| 224 | "data_last_updated": "2011", | 224 | "data_last_updated": "2011", | ||
| 225 | "data_retreival_date": "6/23/2022", | 225 | "data_retreival_date": "6/23/2022", | ||
| 226 | "datastore_active": true, | 226 | "datastore_active": true, | ||
| 227 | "description": "The \"Census PCA Demography - Districts\" | 227 | "description": "The \"Census PCA Demography - Districts\" | ||
| 228 | dataset provides a comprehensive overview of the demography of India | 228 | dataset provides a comprehensive overview of the demography of India | ||
| 229 | at the district level. The data, sourced from the official Census | 229 | at the district level. The data, sourced from the official Census | ||
| 230 | India website, specifically highlights the working status of the | 230 | India website, specifically highlights the working status of the | ||
| 231 | population, categorizing them as main workers, marginal workers, | 231 | population, categorizing them as main workers, marginal workers, | ||
| 232 | non-workers, and those marginal workers/non-workers seeking or | 232 | non-workers, and those marginal workers/non-workers seeking or | ||
| 233 | available for work. It further classifies this information by various | 233 | available for work. It further classifies this information by various | ||
| 234 | criteria such as age, gender, literacy, social group, and | 234 | criteria such as age, gender, literacy, social group, and | ||
| 235 | occupation.", | 235 | occupation.", | ||
| 236 | "district_no": "729", | 236 | "district_no": "729", | ||
| 237 | "format": "CSV", | 237 | "format": "CSV", | ||
| 238 | "frequency": "Decadal", | 238 | "frequency": "Decadal", | ||
| n | n | 239 | "geo_columns": [ | ||
| 240 | "state_code", | ||||
| 241 | "district_code" | ||||
| 242 | ], | ||||
| 239 | "gp_no": "", | 243 | "gp_no": "", | ||
| 240 | "granularity": "District", | 244 | "granularity": "District", | ||
| 241 | "hash": "", | 245 | "hash": "", | ||
| 242 | "id": "efefb405-bd30-4041-bd36-5e6b0d9432ff", | 246 | "id": "efefb405-bd30-4041-bd36-5e6b0d9432ff", | ||
| 243 | "idp_ready": true, | 247 | "idp_ready": true, | ||
| 244 | "last_modified": "2023-10-16T09:35:04.838463", | 248 | "last_modified": "2023-10-16T09:35:04.838463", | ||
| 245 | "lgd_mapping": "yes", | 249 | "lgd_mapping": "yes", | ||
| t | 246 | "metadata_modified": "2024-08-22T10:11:02.441992", | t | 250 | "metadata_modified": "2025-12-19T08:07:54.901528", |
| 247 | "methodology": "The data is collected as part of the national | 251 | "methodology": "The data is collected as part of the national | ||
| 248 | census conducted by the Government of India. Enumerators are trained | 252 | census conducted by the Government of India. Enumerators are trained | ||
| 249 | and deployed across the country to gather detailed demographic | 253 | and deployed across the country to gather detailed demographic | ||
| 250 | information at the household level, which is then aggregated and | 254 | information at the household level, which is then aggregated and | ||
| 251 | reported at various administrative divisions, including at the | 255 | reported at various administrative divisions, including at the | ||
| 252 | district level. This particular dataset focuses on the working | 256 | district level. This particular dataset focuses on the working | ||
| 253 | dynamics of the population, capturing the intricacies of employment, | 257 | dynamics of the population, capturing the intricacies of employment, | ||
| 254 | unemployment, and the nature of jobs people are engaged in.", | 258 | unemployment, and the nature of jobs people are engaged in.", | ||
| 255 | "mimetype": null, | 259 | "mimetype": null, | ||
| 256 | "mimetype_inner": null, | 260 | "mimetype_inner": null, | ||
| 257 | "name": "Census PCA Demography - Districts", | 261 | "name": "Census PCA Demography - Districts", | ||
| 258 | "no_indicators": "1", | 262 | "no_indicators": "1", | ||
| 259 | "package_id": "2a41af7b-7922-4d8f-83c9-d5ebcb8a5f54", | 263 | "package_id": "2a41af7b-7922-4d8f-83c9-d5ebcb8a5f54", | ||
| 260 | "position": 1, | 264 | "position": 1, | ||
| 261 | "resource_type": null, | 265 | "resource_type": null, | ||
| 262 | "similar_resources": "", | 266 | "similar_resources": "", | ||
| 263 | "size": 24554784, | 267 | "size": 24554784, | ||
| 264 | "sku": "moha-census_pca_demography-dt-dc-abc", | 268 | "sku": "moha-census_pca_demography-dt-dc-abc", | ||
| 265 | "state": "active", | 269 | "state": "active", | ||
| 266 | "states_uts_no": "36", | 270 | "states_uts_no": "36", | ||
| 267 | "tehsil_no": "", | 271 | "tehsil_no": "", | ||
| 268 | "url": | 272 | "url": | ||
| 269 | -4041-bd36-5e6b0d9432ff/download/census-pca-demography-districts.csv", | 273 | -4041-bd36-5e6b0d9432ff/download/census-pca-demography-districts.csv", | ||
| 270 | "url_type": "upload", | 274 | "url_type": "upload", | ||
| 271 | "years_covered": "2011.0" | 275 | "years_covered": "2011.0" | ||
| 272 | }, | 276 | }, | ||
| 273 | { | 277 | { | ||
| 274 | "additional_info": "", | 278 | "additional_info": "", | ||
| 275 | "cache_last_updated": null, | 279 | "cache_last_updated": null, | ||
| 276 | "cache_url": null, | 280 | "cache_url": null, | ||
| 277 | "created": "2023-10-16T09:38:04.655836", | 281 | "created": "2023-10-16T09:38:04.655836", | ||
| 278 | "data_extraction_page": "B-01: Main workers, marginal workers, | 282 | "data_extraction_page": "B-01: Main workers, marginal workers, | ||
| 279 | non-workers and those marginal workers, non-workers seeking/available | 283 | non-workers and those marginal workers, non-workers seeking/available | ||
| 280 | for work classified by age and sex", | 284 | for work classified by age and sex", | ||
| 281 | "data_insights": "Data Insights that can be drawn:Distribution | 285 | "data_insights": "Data Insights that can be drawn:Distribution | ||
| 282 | of main workers, marginal workers, and non-workers across different | 286 | of main workers, marginal workers, and non-workers across different | ||
| 283 | states, districts, and blocks.Analysis of the population | 287 | states, districts, and blocks.Analysis of the population | ||
| 284 | seeking/available for work based on age and gender.Literacy rates | 288 | seeking/available for work based on age and gender.Literacy rates | ||
| 285 | among different worker types and social groups.Occupation trends | 289 | among different worker types and social groups.Occupation trends | ||
| 286 | across various demographic groups.Understanding of the distribution of | 290 | across various demographic groups.Understanding of the distribution of | ||
| 287 | the population based on rural or urban settings.Gender-based analysis | 291 | the population based on rural or urban settings.Gender-based analysis | ||
| 288 | of different working statuses, occupations, and literacy | 292 | of different working statuses, occupations, and literacy | ||
| 289 | rates.Insights into the distribution of different social groups in the | 293 | rates.Insights into the distribution of different social groups in the | ||
| 290 | working population.Age-wise distribution of the workforce, including | 294 | working population.Age-wise distribution of the workforce, including | ||
| 291 | those seeking employment.", | 295 | those seeking employment.", | ||
| 292 | "data_last_updated": "2011", | 296 | "data_last_updated": "2011", | ||
| 293 | "data_retreival_date": "6/23/2022", | 297 | "data_retreival_date": "6/23/2022", | ||
| 294 | "datastore_active": true, | 298 | "datastore_active": true, | ||
| 295 | "description": "The \"Census PCA Demography - Blocks\" dataset | 299 | "description": "The \"Census PCA Demography - Blocks\" dataset | ||
| 296 | offers detailed demographic insights into the working population of | 300 | offers detailed demographic insights into the working population of | ||
| 297 | India. Sourced from the official Census India website, this dataset | 301 | India. Sourced from the official Census India website, this dataset | ||
| 298 | primarily focuses on different worker classifications based on various | 302 | primarily focuses on different worker classifications based on various | ||
| 299 | demographic factors such as age, gender, and social group. It covers | 303 | demographic factors such as age, gender, and social group. It covers | ||
| 300 | data at the granular level of individual blocks within sub-districts, | 304 | data at the granular level of individual blocks within sub-districts, | ||
| 301 | districts, and states.", | 305 | districts, and states.", | ||
| 302 | "district_no": "729", | 306 | "district_no": "729", | ||
| 303 | "format": "CSV", | 307 | "format": "CSV", | ||
| 304 | "frequency": "Decadal", | 308 | "frequency": "Decadal", | ||
| 305 | "gp_no": "", | 309 | "gp_no": "", | ||
| 306 | "granularity": "Village", | 310 | "granularity": "Village", | ||
| 307 | "hash": "", | 311 | "hash": "", | ||
| 308 | "id": "80a2520f-40ae-4cbc-8ee5-bead9ae81ace", | 312 | "id": "80a2520f-40ae-4cbc-8ee5-bead9ae81ace", | ||
| 309 | "idp_ready": true, | 313 | "idp_ready": true, | ||
| 310 | "last_modified": "2023-10-16T09:38:04.630156", | 314 | "last_modified": "2023-10-16T09:38:04.630156", | ||
| 311 | "lgd_mapping": "yes", | 315 | "lgd_mapping": "yes", | ||
| 312 | "metadata_modified": "2024-08-22T10:11:03.060819", | 316 | "metadata_modified": "2024-08-22T10:11:03.060819", | ||
| 313 | "methodology": "The dataset is derived from the Population | 317 | "methodology": "The dataset is derived from the Population | ||
| 314 | Census, an extensive exercise conducted by the Government of India to | 318 | Census, an extensive exercise conducted by the Government of India to | ||
| 315 | count and characterize its population. The data collection process is | 319 | count and characterize its population. The data collection process is | ||
| 316 | standardized, with enumerators visiting households and collecting data | 320 | standardized, with enumerators visiting households and collecting data | ||
| 317 | on various aspects of the population, including their working status. | 321 | on various aspects of the population, including their working status. | ||
| 318 | This particular subset focuses on classifying the working population | 322 | This particular subset focuses on classifying the working population | ||
| 319 | based on the criteria mentioned in the data columns.", | 323 | based on the criteria mentioned in the data columns.", | ||
| 320 | "mimetype": null, | 324 | "mimetype": null, | ||
| 321 | "mimetype_inner": null, | 325 | "mimetype_inner": null, | ||
| 322 | "name": "Census PCA Demography - Blocks", | 326 | "name": "Census PCA Demography - Blocks", | ||
| 323 | "no_indicators": "1", | 327 | "no_indicators": "1", | ||
| 324 | "package_id": "2a41af7b-7922-4d8f-83c9-d5ebcb8a5f54", | 328 | "package_id": "2a41af7b-7922-4d8f-83c9-d5ebcb8a5f54", | ||
| 325 | "position": 2, | 329 | "position": 2, | ||
| 326 | "resource_type": null, | 330 | "resource_type": null, | ||
| 327 | "similar_resources": "", | 331 | "similar_resources": "", | ||
| 328 | "size": 281834931, | 332 | "size": 281834931, | ||
| 329 | "sku": "moha-census_pca_demography-bl-dc-abc", | 333 | "sku": "moha-census_pca_demography-bl-dc-abc", | ||
| 330 | "state": "active", | 334 | "state": "active", | ||
| 331 | "states_uts_no": "36", | 335 | "states_uts_no": "36", | ||
| 332 | "tehsil_no": "7127", | 336 | "tehsil_no": "7127", | ||
| 333 | "url": | 337 | "url": | ||
| 334 | 0ae-4cbc-8ee5-bead9ae81ace/download/census-pca-demography-blocks.csv", | 338 | 0ae-4cbc-8ee5-bead9ae81ace/download/census-pca-demography-blocks.csv", | ||
| 335 | "url_type": "upload", | 339 | "url_type": "upload", | ||
| 336 | "years_covered": "2011.0" | 340 | "years_covered": "2011.0" | ||
| 337 | }, | 341 | }, | ||
| 338 | { | 342 | { | ||
| 339 | "additional_info": "nan", | 343 | "additional_info": "nan", | ||
| 340 | "cache_last_updated": null, | 344 | "cache_last_updated": null, | ||
| 341 | "cache_url": null, | 345 | "cache_url": null, | ||
| 342 | "created": "2023-10-16T10:24:22.677540", | 346 | "created": "2023-10-16T10:24:22.677540", | ||
| 343 | "data_extraction_page": "B-01: Main workers, marginal workers, | 347 | "data_extraction_page": "B-01: Main workers, marginal workers, | ||
| 344 | non-workers and those marginal workers, non-workers seeking/available | 348 | non-workers and those marginal workers, non-workers seeking/available | ||
| 345 | for work classified by age and sex", | 349 | for work classified by age and sex", | ||
| 346 | "data_insights": "Data Insights that can be drawn:\nDemographic | 350 | "data_insights": "Data Insights that can be drawn:\nDemographic | ||
| 347 | Distribution: Analysis can be done on the age and gender distribution | 351 | Distribution: Analysis can be done on the age and gender distribution | ||
| 348 | across various states, districts, and sub-districts. This will reveal | 352 | across various states, districts, and sub-districts. This will reveal | ||
| 349 | the age-wise and gender-wise distribution of the working | 353 | the age-wise and gender-wise distribution of the working | ||
| 350 | population.\nUrban vs Rural Dynamics: By analyzing the 'rural_urban' | 354 | population.\nUrban vs Rural Dynamics: By analyzing the 'rural_urban' | ||
| 351 | column, insights can be drawn regarding the workforce distribution in | 355 | column, insights can be drawn regarding the workforce distribution in | ||
| 352 | urban versus rural areas.\nSocio-Economic Insights: The literacy rate | 356 | urban versus rural areas.\nSocio-Economic Insights: The literacy rate | ||
| 353 | and affiliation to various social groups can provide insights into the | 357 | and affiliation to various social groups can provide insights into the | ||
| 354 | socio-economic conditions of the working population in various | 358 | socio-economic conditions of the working population in various | ||
| 355 | regions.\nOccupation Distribution: The 'occupation' column can help | 359 | regions.\nOccupation Distribution: The 'occupation' column can help | ||
| 356 | identify the primary sources of employment in different | 360 | identify the primary sources of employment in different | ||
| 357 | regions.\nWorker Classification: By studying the 'worker_type' and | 361 | regions.\nWorker Classification: By studying the 'worker_type' and | ||
| 358 | 'working_status' columns, insights can be obtained about the | 362 | 'working_status' columns, insights can be obtained about the | ||
| 359 | percentage of main workers, marginal workers, and non-workers across | 363 | percentage of main workers, marginal workers, and non-workers across | ||
| 360 | regions.", | 364 | regions.", | ||
| 361 | "data_last_updated": "2011", | 365 | "data_last_updated": "2011", | ||
| 362 | "data_retreival_date": "6/23/2022", | 366 | "data_retreival_date": "6/23/2022", | ||
| 363 | "datastore_active": true, | 367 | "datastore_active": true, | ||
| 364 | "description": "The \"Census PCA Demography - Subdistricts\" | 368 | "description": "The \"Census PCA Demography - Subdistricts\" | ||
| 365 | dataset provides a comprehensive overview of the working population | 369 | dataset provides a comprehensive overview of the working population | ||
| 366 | demographics across different subdistricts in India. This dataset is | 370 | demographics across different subdistricts in India. This dataset is | ||
| 367 | sourced from the official Census India website, focusing on main | 371 | sourced from the official Census India website, focusing on main | ||
| 368 | workers, marginal workers, and non-workers. It also offers insights | 372 | workers, marginal workers, and non-workers. It also offers insights | ||
| 369 | into those seeking or available for work, categorized by age and sex. | 373 | into those seeking or available for work, categorized by age and sex. | ||
| 370 | The dataset further dives deep into the socio-economic aspects of the | 374 | The dataset further dives deep into the socio-economic aspects of the | ||
| 371 | population, considering literacy levels, social group affiliation, and | 375 | population, considering literacy levels, social group affiliation, and | ||
| 372 | type of occupation, to provide a holistic perspective.", | 376 | type of occupation, to provide a holistic perspective.", | ||
| 373 | "district_no": "729", | 377 | "district_no": "729", | ||
| 374 | "format": "CSV", | 378 | "format": "CSV", | ||
| 375 | "frequency": "Decadal", | 379 | "frequency": "Decadal", | ||
| 376 | "gp_no": "", | 380 | "gp_no": "", | ||
| 377 | "granularity": "Sub District", | 381 | "granularity": "Sub District", | ||
| 378 | "hash": "", | 382 | "hash": "", | ||
| 379 | "id": "cd430261-1492-4a58-9e65-d6021f8aafdd", | 383 | "id": "cd430261-1492-4a58-9e65-d6021f8aafdd", | ||
| 380 | "idp_ready": true, | 384 | "idp_ready": true, | ||
| 381 | "last_modified": "2024-06-04T06:30:36.148151", | 385 | "last_modified": "2024-06-04T06:30:36.148151", | ||
| 382 | "lgd_mapping": "yes", | 386 | "lgd_mapping": "yes", | ||
| 383 | "metadata_modified": "2024-08-22T10:11:03.689492", | 387 | "metadata_modified": "2024-08-22T10:11:03.689492", | ||
| 384 | "methodology": "The data has been collected by the official | 388 | "methodology": "The data has been collected by the official | ||
| 385 | Census body of India, adhering to standardized census-taking methods | 389 | Census body of India, adhering to standardized census-taking methods | ||
| 386 | and practices. Given the scope of the dataset (spanning across states, | 390 | and practices. Given the scope of the dataset (spanning across states, | ||
| 387 | districts, and sub-districts), there's a multi-tiered approach in data | 391 | districts, and sub-districts), there's a multi-tiered approach in data | ||
| 388 | collection, which is then categorized by various parameters such as | 392 | collection, which is then categorized by various parameters such as | ||
| 389 | rural or urban setting, age, gender, etc. The methodology ensures a | 393 | rural or urban setting, age, gender, etc. The methodology ensures a | ||
| 390 | thorough representation of the diverse Indian population and its | 394 | thorough representation of the diverse Indian population and its | ||
| 391 | workforce.", | 395 | workforce.", | ||
| 392 | "mimetype": "text/csv", | 396 | "mimetype": "text/csv", | ||
| 393 | "mimetype_inner": null, | 397 | "mimetype_inner": null, | ||
| 394 | "name": "Census PCA Demography - Subdistricts", | 398 | "name": "Census PCA Demography - Subdistricts", | ||
| 395 | "no_indicators": "1", | 399 | "no_indicators": "1", | ||
| 396 | "package_id": "2a41af7b-7922-4d8f-83c9-d5ebcb8a5f54", | 400 | "package_id": "2a41af7b-7922-4d8f-83c9-d5ebcb8a5f54", | ||
| 397 | "position": 3, | 401 | "position": 3, | ||
| 398 | "resource_type": null, | 402 | "resource_type": null, | ||
| 399 | "similar_datasets": [], | 403 | "similar_datasets": [], | ||
| 400 | "similar_resources": "", | 404 | "similar_resources": "", | ||
| 401 | "size": 176506080, | 405 | "size": 176506080, | ||
| 402 | "sku": "moha-census_pca_demography-sd-dc-abc", | 406 | "sku": "moha-census_pca_demography-sd-dc-abc", | ||
| 403 | "state": "active", | 407 | "state": "active", | ||
| 404 | "states_uts_no": "36", | 408 | "states_uts_no": "36", | ||
| 405 | "tags": [ | 409 | "tags": [ | ||
| 406 | "Census", | 410 | "Census", | ||
| 407 | "Demography", | 411 | "Demography", | ||
| 408 | "Workforce Analysis", | 412 | "Workforce Analysis", | ||
| 409 | "Literacy", | 413 | "Literacy", | ||
| 410 | "Social Groups", | 414 | "Social Groups", | ||
| 411 | "Rural-Urban Divide", | 415 | "Rural-Urban Divide", | ||
| 412 | "Population Distribution", | 416 | "Population Distribution", | ||
| 413 | "Geographic Distribution", | 417 | "Geographic Distribution", | ||
| 414 | "Age Distribution" | 418 | "Age Distribution" | ||
| 415 | ], | 419 | ], | ||
| 416 | "tehsil_no": "", | 420 | "tehsil_no": "", | ||
| 417 | "url": | 421 | "url": | ||
| 418 | 58-9e65-d6021f8aafdd/download/census-pca-demography-subdistricts.csv", | 422 | 58-9e65-d6021f8aafdd/download/census-pca-demography-subdistricts.csv", | ||
| 419 | "url_type": "upload", | 423 | "url_type": "upload", | ||
| 420 | "years_covered": "2011.0" | 424 | "years_covered": "2011.0" | ||
| 421 | } | 425 | } | ||
| 422 | ], | 426 | ], | ||
| 423 | "sector": [ | 427 | "sector": [ | ||
| 424 | "Socio Economic" | 428 | "Socio Economic" | ||
| 425 | ], | 429 | ], | ||
| 426 | "source_name": "Registrar General of India and Ministry of Home | 430 | "source_name": "Registrar General of India and Ministry of Home | ||
| 427 | Affairs (MHA)", | 431 | Affairs (MHA)", | ||
| 428 | "state": "active", | 432 | "state": "active", | ||
| 429 | "title": "Census PCA Demography", | 433 | "title": "Census PCA Demography", | ||
| 430 | "type": "dataset", | 434 | "type": "dataset", | ||
| 431 | "url": | 435 | "url": | ||
| 432 | "https://censusindia.gov.in/census.website/data/census-tables", | 436 | "https://censusindia.gov.in/census.website/data/census-tables", | ||
| 433 | "version": null | 437 | "version": null | ||
| 434 | } | 438 | } |