Analysis of ‘India Census 2011’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/danofer/india-census on 13 February 2022.

--- Dataset description provided by original source is as follows ---

Context

2011 India census data. Includes population/demographic data and housing data for each district.

Content

• india-districts-census-2011.csv - Population enumeration data with expanded columns.
• hlpca-total.csv: Housing statistics for total (rural + urban) population by district.
• pca-colnames.csv: Mapping of PCA column names to expanded names.

Data is raw counts per district, not normalized percentages!

Acknowledgements

Gathered from 2 sources: https://github.com/pigshell/india-census-2011 https://github.com/nishusharma1608/India-Census-2011-Analysis

Original census data released (and owned by) the Registrar General and Census Commissioner of India under the Ministry of Home Affairs, Government of India.

Inspiration

• Where are differences between urbal and rural areas greatest? Between casts? Between men and women?
• Use data with other datasets in India!

--- Original source retains full ownership of the source dataset ---

This dataset provides a final result census of the population in the Kingdom of Cambodia in 2019, which shows the total population, total population of males and females, total households, household size, density and areas by provinces in the Kingdom of Cambodia. This dataset is extracted from a section of original document of General population census of the Kingdom of Cambodia 2019 national report on final census results by the National Institute of Statistics of the Ministry of Planning.

This dataset comprises the adjustments to Census 2011 for England

This dataset comprises the adjustments to Census 2011 for England

The map shows the distribution of the population by census subdivision who identified themselves in the 2006 Census as North American Indian. According to the 2006 Census, 698 025 people identified themselves as North American Indian also referred to as 'First Nations people'.

Description:

Since 2009, the departmental directorate of the Marne territories has been carrying out a census of the land resources available within the main urban areas of the Marne. This census concerns land rights of way for known or probable brownfields of all types (industrial, railway, military, etc.). The area retained for brownfields is 2 000 m², threshold defined as potentially an issue. This census is not exhaustive. Census conducted until October 2018.

Genealogy:

A first census of brownfields was carried out from the databases of the Ministry of Ecology, Sustainable Development and Energy “BASIAS” and “Basol”, listing polluted sites. Visits by the territorial referents (RT) of the departmental directorate of the territories were then carried out on site and made it possible to complete the first census. The data is geolocated in the form of polygons using the parcelal cD (default of digitised cadastre).

Metadata: ID: identification of wasteland by number ENTITE: current state (fridge or wasteland converted) CD_INSEE: INSEE code NOM_COM: name of the municipality DESCRIPTION: current state of land or built at census date ACTIV: past or new activity for brownfields ENTER: name of company and/or owner, who is or was installed ADDRESS: address of the wasteland PROJECT: project in progress at census date if known COMMENT: further information on the situation of the wasteland at the last date of its census. SOURCE: Source of information. Date_MAJ: date of update

The geolocation data is in the form of a polygon.

The data refers to details of Area Name, Total/Rural/Urban, Type of Census Houses Total number of census houses, Permanent, Semi-permanent, Temporary Total, Temporary Serviceable, Temporary Non Serviceable, Unclassifiable at States/UTs and District level.

The catalog contains data related to population classified by place of birth and sex, census 2001 - India and States. It includes data on Population by Place of Birth, Population by Sex, Population Classified by Place of Birth, Population Classified by Sex, Population by Place of Birth and Sex, Population Classified by Place of Birth and Sex, Population Born in India, Population Born Within the State of Enumeration, Population Born in the Place of Enumeration, Population Born in Other Districts of the State, Population Born in Other States in India, Census 2001.

2014 Myanmar Census Department of Population, Ministry of Immigration and Population

As of May 15, 2001, 5.4 million people, or 18.4% of the total population, were born outside the country. This was the highest proportion since 1931, when foreign-born people made up 22.2% of the population. In 1996, the proportion was 17.4%. The map shows the percentage of the total population that was foreign-born by census division.

Canada was home to almost 4 million individuals who identified themselves as visible minorities in 2001, accounting for 13.4% of the total population. The proportion of the visible minority population has increased steadily over the past 20 years. In 1981, 1.1 million visible minorities accounted for 4.7% of the total population; by 1996, 3.2 million accounted for 11.2%.

The map shows the distribution of the population by census subdivision who identified themselves in the 2006 Census as Inuit. According to the 2006 Census, 50 485 people identified themselves as Inuit.

Census of pharmacies in Aveyron from the FINESS database (Ministry of Health), health establishments corresponding to categories 620, 628 and 629. Geocoding at the address. Lambert 93 — Date of data: 01/08/2010

This vector dataset provides the population density by commune in Cambodia, as provided by Cambodian Demographic Census 2008 (Ministry of Planning, National Institute of Statistics). Dataset were provided to Open Development Cambodia (ODC) in vector format by Save Cambodia's Wildlife's Atlas Working Group.

This dataset presents national-level literacy rates, compiled from multiple official sources, including the National Sample Survey (NSS), Periodic Labour Force Survey (PLFS), Population Census, National Family Health Survey (NFHS), and data published by the Ministry of Statistics and Programme Implementation (MoSPI).

It provides literacy rates disaggregated by gender, region (urban and rural), and age group. The inclusion of age groups is essential, as the criteria for calculating literacy rates have changed over time. To allow consistent comparisons across sources and years, an ‘age group’ column is included in the dataset. In general, literacy is assessed based on whether a person above a specified age can read and write a simple message with understanding in at least one language. The age specified as per these sources is as follows:

Census: Population aged 7 years and above (used since 1981; previously, it was 5 years and above). Data is available for 1951, 1961, 1971, 1981, 1991, 2001, and 2011 NSS: Population aged 5 years and above. Data is available for 2005, 2007-08, 2010, 2011-12, 2014, and 2017-18 PLFS: Survey typically covers population aged 15 years and above, but literacy data is also available for 5 years and above and 7 years and above. Data is available for 2017-18 to 2023-24. NFHS: Covers population aged 15–49 years only. Literacy rate refers to women and men who have completed standard 6, 9, or higher, or those who can read a full or partial sentence among individuals assumed to be literate. Data is available for 2005-06, 2015-16, and 2019-21. MoSPI: Follows the NSS age criteria, usually 5 years and above. Data is available for 2003, 2004, 2006, 2007, and 2011

Abstract

Since the 1980s, the Peruvian government has conducted significant data-collection efforts to characterize the country’s artisanal fisheries sector. In 1982, the Fisheries Ministry identified 181 disembarkment sites along the 3,000 kilometres of coastlines. The Ocean’s Institute conducted two surveys of artisanal fisheries in 1996 and 2005 to obtain information on fishing activities, socioeconomic and cultural levels, and track changes over time. Between 2002 and 2003, the Ministry of Production launched a system to collect data on the disembarkment of artisanal fishing from the coast. These studies were carried out mainly in coastal zones, an area that explains more than 90% of the landings of hydrobiological resources, which have filled a great gap in the need to characterize Peruvian artisanal fishing. However, it is still an essential need to carry out a census that allows accurate and updated data to be obtained from a population that shows high rates of variation, dispersion and mobilization.

The I National Census of Artisanal Fisheries in the Maritime Sphere 2012, was conducted in the coast of Tumbes, Piura, Lambayeque, La Libertad, Ancash, Lima, Ica, Arequipa, Moquegua, Tacna and the Constitutional Province of Callao, registering fishermen and craft shipowners at the place where they were at the time of the census, regardless of their habitual residence. The general objective of the census is to collect, process and present basic, economic, up-to-date and reliable statistical information about fishermen, shipowners, vessels, landing points and shipyards for the construction of artisanal fishing vessels on the Peruvian coast.

Geographic coverage

Tumbes Piura Lambayaque Ancash Moquegua Arequipa Ica Lima Provincias Norte Lima Provincias Sur Lima y Callao

Analysis unit

Artisanal fishermen, Landing points, artisanal fishing shipyards and artisanal naval carpentries, artisanal boat builders

Universe

• 44,161 Artisanal Fishermen
• 16,045 Owners of artisanal fishing vessels
• 116 Landing points
• 138 Artisanal Fishing Shipyards
• 46 Artisanal Naval Carpentries

Kind of data

census data [cen]

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

PROCESSING

To ensure the dissemination or reliable and timely information, data processing is centralized at INEI headquarters and processes are systemized. The process begins with the development of data entry and consistency software, digitization of information, the respective processing, and finally ensuring a consistent, coherent, reliable, and timely database is achieved.

I. Development of the Software

This step refers to preparing the necessary software for data entry, form processing, and to check the consistency of the datasets and collected in I CENPAR. Software is also used to support other activities such as hiring of personnel, monitoring and follow-up activities and processes, document control, repository of questions and answers, and administration of look-up tables

II. Data processing

The information on the completed forms is entered manually into the database. An intelligent data entry program was designed that contemplates all the variables of the census forms.

DATA CONSISTENCY

It comprises the implementation of a set of tasks that aim to ensure that the census information collected is coherent and consistent. The task also includes coding, which consists of assigning numerical keys or codes to the information in open questions, which allows the information to be processed electronically. Consistency checks will be carried out by electronic means. There are a set of rules and relationships that the data collected must comply with. In the event that such relationships do not hold, the corresponding amendments to the data must be made.

GENERATION OF THE DATABASE

the information is organized in a relational model. This model allows basic information to be retrieved from the microdata at the level of the statistical units by geographic location, category of the landing point, among others.

Abstract

The current India Agriculture Census with reference year 2010-11 is ninth in the series.

The Department of Agriculture and Cooperation, Ministry of Agriculture, Government of India conducts Agriculture Census, quinquennially, to collect data on operational holdings in the country. The reference period for Agriculture Census is the Agricultural year (July-June). Being the ultimate unit for taking agriculture-related decisions, operational holding has been taken as statistical unit at micro-level for data collection.

The Agriculture Census was conducted in three distinct Phases. The provisional results for first Phase of the current Census were released at State and all India level in October, 2012. After, scrutinizing the results at District/Tehsil level, this database has now been finalized and is being published in the form of an All India Report on number and area of operational holdings.

The main objectives of the Agriculture Census are: i) To describe structure and characteristics of agriculture by providing statistical data on operational holdings, including land utilization, irrigation, source of irrigation, irrigated and unirrigated area under different crops, live-stock, agricultural machinery and implements, use of fertilizers, seeds, agricultural credit etc. ii) To provide benchmark data needed for formulating new agricultural development programmes and for evaluating their progress. iii) To provide basic frame of operational holdings for carrying out future agricultural surveys and, iv) To lay a basis for developing an integrated programme for current agricultural statistics.

Geographic coverage

National

Analysis unit

Agricultural household, individual

Kind of data

Census/enumeration data [cen]

Sampling procedure

The Agriculture Census data is collected following two broad approaches; in States where comprehensive land records exist (Land Record States), for Phase-I of the Census, the data on primary characteristics of operational holdings are collected and compiled on complete enumeration basis through re-tabulation of information available in the Village Land Records. For other States (Non-Land record States), this data is collected on sample basis following household enquiry.

In land record States,data on Agriculture Census is pooled for all the parcels of an operational holding irrespective of its location. However, for operational convenience, the outer limit for pooling is restricted to taluka. This pooling is done for each operational holder in the village of his residence. In the non-land record States, the data is collected through sample survey in 20 per cent of villages in each block. These villages are selected through simple random sampling method and all the operational holdings in the selected villagesare enumerated following household enquiry approach.

In smaller UTs, like Lakshadweep, Daman & Diu etc., no sampling is done. i.e. all holdings in all the villages are surveyed for collection of data.

Mode of data collection

Face-to-face [f2f]

2011 census of licences from sports federations approved by the Ministry in charge of sports.\ The dataset presents by city and federation the number of

graduates in the Yvelines, women, under the age of 20, over 60 years,

Insee population data.\

The data are geocoded (common).\

(Source Ministry of Sport, 23 Sept. 2013)

This data set is no longer compiled by the Ministry of the Solicitor General. Data from the Police Administration Survey. Describes the police strength (number of police officers per 100,000 people) in Ontario's census metropolitan areas. These are areas with: * At least 100,000 total residents * At least 50,000 residents in the core Data is based on the number of police officers in 2012 and populations for 2011. The data can be accessed from Statistics Canada.

Nearly 74% of Canadian commuters drove to work in 2001, up from 73.3% and about 10.5% of employed Canadians used public transportation to get to work in 2001, up marginally from 10.1% in 1996. In 2001, the proportion of workers who rode to work as passengers in a car, truck or van decreased to 6.9% from 7.4% in 1996. About 6.6% of all employed Canadians walked to work in 2001, down slightly from 7.0% in 1996. The proportion of employed Canadians who cycled to work increased marginally to 1.2% in 2001 from 1.1% in 1996.

"Those data are part of work to collect data about the status of coastal migratory flyway populations of the East Atlantic Flyway (van Roomen et al. 2013) and of partial migratory or resident waterbird populations using the same sites at this flyway. It is organized by the Wadden Sea Flyway Initiative, Wetlands International and BirdLife International in cooperation with national authorities, organisations and institutions responsible for waterbird and wetland monitoring. Besides national investments of the monitoring partners, it was funded by the Dutch Ministry of Economic Affairs through Programme Rich Wadden Sea, the organisation MAVA through BirdLife International and Wetlands International, The World Wide Fund for Nature in The Netherlands, The National Park Wadden Sea Schleswig-Holstein through the Common Wadden Sea Secretariat, The National Park Wadden Sea Niedersachsen, Vogelbescherming The Netherlands and the WeBS partnership from the UK."