This dataset provides a comprehensive look at population and migration trends in five South Asian countries: Afghanistan, Bangladesh, India, Pakistan, and Sri Lanka, covering the years 1960 to 2023. The data is sourced directly from the World Bank API and contains detailed statistics on total population and net migration for each year.

This dataset is ideal for:

• Time-series analysis to study population trends over six decades.
• Migration studies to assess policy impacts and demographic shifts.
• Data visualization for dashboards and presentations.
• Machine learning applications in predictive analytics.

Columns: - Country: Name of the country. - Year: Year of the recorded data. - Total Population: The total population of the country. - Net Migration: Net migration balance (positive for immigration surplus, negative for emigration surplus).

Key Insights: - Afghanistan: Significant migration shifts due to conflicts and crises. - India: Continuous population growth with varying migration trends. - Bangladesh: A history of large emigration and its impact on demographics. - Pakistan: Migration surpluses in some years and large outflows in others. - Sri Lanka: Gradual population growth and consistent emigration patterns.

Context

This dataset is a comprehensive guide aimed at assisting individuals from Pakistan, India, and other regions who are planning to migrate abroad. It features detailed profiles of 48 countries, outlining key factors such as visa requirements, employment opportunities, educational prospects, and cultural insights. Originating from Dr. Zeeshan Usmani's influential YouTube series "Chalo Chalo," which aired between July 22, 2023, and October 27, 2024, this dataset captures essential insights for potential migrants to make informed decisions about their destination country.

Content

Geography: Global

Time period: July 2023 – October 2024

Unit of analysis: Countries

Dataset: The dataset includes information on 48 countries with a focus on helping skilled individuals from Pakistan and India explore opportunities abroad. Each entry provides data on visa processes, job applications, educational opportunities, and cultural assimilation. Dr. Usmani, leveraging his vast experiences and academic achievements, aims to provide mentorship and guidance through these entries.

Variables: Country, visa requirements, employment opportunities, educational prospects, cultural insights, and strategic relocation advice.

File Type: CSV

Acknowledgements

Special thanks to Dr. Zeeshan Usmani, Global Director of Data Science and Partnerships at Walee, for not only inspiring this project but also for his dedication to guiding aspiring migrants through his "Chalo Chalo" Youtube video series. His commitment to using data to empower individuals is evident in every piece of this dataset.

Youtube Playlist Link: https://www.youtube.com/watch?v=SCEPZS-eeNQ&list=PLJD-996ceLKaIoEs80Vn3Zp1DfMxxsc0X&index=1

Inspiration

This dataset invites researchers, data scientists, and policymakers to explore several avenues:

• Assess Professional Demand: Examine the demand for specific professions and skills across various countries to inform career decision-making for potential migrants.

• Cultural Adaptation Analysis: Analyze "Country Culture" data to identify cultural similarities and differences, aiding migrants in selecting destinations that may facilitate easier cultural integration.

• Safety Perception Impact: Explore how perceived safety, as detailed in the "Safety" column, affects the attractiveness of countries as potential migration destinations.

• Educational Opportunities Evaluation: Investigate the "Educational Opportunities" in each country to identify and highlight regions offering significant educational benefits, crucial for student migrants.

• Migration Trends and Forecasting: Utilize data on visa types and migration policies to identify trends and predict future migration patterns, enhancing migration strategy and planning.

This guide is intended to be a dynamic resource that will grow and evolve with the addition of new insights from future episodes of the "Chalo Chalo" series. It stands as a testament to the power of data in transforming the personal and professional lives of individuals looking to navigate the complexities of global migration.

Census: Number of Migrants: Maharashtra data was reported at 57,376,776.000 Person in 03-01-2011. This records an increase from the previous number of 41,715,711.000 Person for 03-01-2001. Census: Number of Migrants: Maharashtra data is updated decadal, averaging 41,715,711.000 Person from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 57,376,776.000 Person in 03-01-2011 and a record low of 25,462,420.000 Person in 03-01-1991. Census: Number of Migrants: Maharashtra data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAG001: Census of India: Migration: Number of Migrants: by States.

Census: Number of Migrants: Punjab data was reported at 13,735,616.000 Person in 03-01-2011. This records an increase from the previous number of 9,189,438.000 Person for 03-01-2001. Census: Number of Migrants: Punjab data is updated decadal, averaging 9,189,438.000 Person from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 13,735,616.000 Person in 03-01-2011 and a record low of 6,960,431.000 Person in 03-01-1991. Census: Number of Migrants: Punjab data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAG001: Census of India: Migration: Number of Migrants: by States.

Inspiration

Inspired by another Kaggle user who did a similar project with Indian emigrants (https://www.kaggle.com/rajacsp/indian-migration-history)

Content

Data sourced from World Bank database at https://datacatalog.worldbank.org/dataset/global-bilateral-migration-database. In addition to selecting the decades from 1960-2000, I added a "Total" column and a least squares regression rate column. The original CSV (SG_IMMIGRANTS.csv) is a bit messy and contains a lot of blanks because ... well Singapore is a small country.

For the two limited "melted" versions, I used pandas pd.melt() to restructure the different decades into a new column "Year" with it's corresponding "Total". Only a select few countries with substantial number of total immigrants are included (Bangladesh, China, Indonesia, Pakistan, Thailand, Philippines, India, Malaysia, Vietnam, United Kingdom). Here, the ratio refers to either the ratio of gender to decade's total or the ratio of that decade's total to the country's all-time cumulative total . e.g. Male 1960 CHN Ratio =0.510563203 means males made up 51% of the total Chinese immigrants to SG in 1960 e.g. Total 1960 MYS Ratio = 0.081202409 means 1960 contributed only 8% of the total Malaysian immigrants to SG

Hope this is clear, leave a comment if anything needs clarification!

Thoughts/to-do:

Future version with global database csv, SG emigrants csv For select top origin/destination countries, show a positive-negative bar plot, coloured according to immigration/emigration multiple

Census: Number of Migrants: West Bengal data was reported at 33,448,472.000 Person in 03-01-2011. This records an increase from the previous number of 25,097,629.000 Person for 03-01-2001. Census: Number of Migrants: West Bengal data is updated decadal, averaging 25,097,629.000 Person from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 33,448,472.000 Person in 03-01-2011 and a record low of 17,870,781.000 Person in 03-01-1991. Census: Number of Migrants: West Bengal data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAG001: Census of India: Migration: Number of Migrants: by States.

This table contains 25 series, with data for years 1955 - 2013 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...) Last permanent residence (25 items: Total immigrants; France; Great Britain; Total Europe ...).

The human population history in Southeast Asia was shaped by numerous migrations and population expansions. Their reconstruction based on archaeological, linguistic or human genetic data is often hampered by the limited number of informative polymorphisms in classical human genetic markers, such as the hypervariable regions of the mitochondrial DNA. Here, we analyse housekeeping gene sequences of the human stomach bacterium Helicobacter pylori from various countries in Southeast Asia and we provide evidence that H. pylori accompanied at least three ancient human migrations into this area: i) a migration from India introducing hpEurope bacteria into Thailand, Cambodia and Malaysia; ii) a migration of the ancestors of Austro-Asiatic speaking people into Vietnam and Cambodia carrying hspEAsia bacteria; and iii) a migration of the ancestors of the Thai people from Southern China into Thailand carrying H. pylori of population hpAsia2. Moreover, the H. pylori sequences reflect iv) the migrations of Chinese to Thailand and Malaysia within the last 200 years spreading hspEasia strains, and v) migrations of Indians to Malaysia within the last 200 years distributing both hpAsia2 and hpEurope bacteria. The distribution of the bacterial populations seems to strongly influence the incidence of gastric cancer as countries with predominantly hspEAsia isolates exhibit a high incidence of gastric cancer while the incidence is low in countries with a high proportion of hpAsia2 or hpEurope strains. In the future, the host range expansion of hpEurope strains among Asian populations, combined with human motility, may have a significant impact on gastric cancer incidence in Asia.

Census: Number of Migrants: Delhi data was reported at 7,224,514.000 Person in 03-01-2011. This records an increase from the previous number of 6,014,458.000 Person for 03-01-2001. Census: Number of Migrants: Delhi data is updated decadal, averaging 6,014,458.000 Person from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 7,224,514.000 Person in 03-01-2011 and a record low of 3,723,462.000 Person in 03-01-1991. Census: Number of Migrants: Delhi data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAG001: Census of India: Migration: Number of Migrants: by States.

Abstract

An effective policy response to the economic impacts of the COVID-19 pandemic requires an enormous range of data to inform the design and response of programs. Public health measures require data on the spread of the disease, beliefs in the population, and capacity of the health system. Relief efforts depend on an understanding of hardships being faced by various segments of the population. Food policy requires measurement of agricultural production and hunger. In such a rapidly evolving pandemic, these data must be collected at a high frequency. Given the unexpected nature of the shock and urgency with which a response was required, Indian policymakers needed to formulate policies affecting India's 1.4 billion people, without the detailed evidence required to construct effective programs. To help overcome this evidence gap, researchers from the World Bank, in collaboration with IDinsight, the Development Data Lab, and John Hopkins University sought to produce rigorous and responsive data for policymakers across six states in India: Jharkhand, Rajasthan, Uttar Pradesh, Andhra Pradesh, Bihar, and Madhya Pradesh.

Geographic coverage

Regional coverage

Analysis unit

Households

Universe

Households located in Jharkhand, Rajasthan, Uttar Pradesh, Andhra Pradesh, Bihar, and Madhya Pradesh

Kind of data

Sample survey data [ssd]

Sampling procedure

This dataset includes observations covering six states (Andhra Pradesh, Bihar, Jharkhand, Madhya Pradesh, Rajasthan, Uttar Pradesh) and three survey rounds. The survey did not have a single, unified frame from which to sample phone numbers. The final sample was assembled from several different sample frames, and the choice of frame sample frames varied across states and survey rounds.

These frames comprise four prior IDinsight projects and from an impact evaluation of the National Rural Livelihoods project conducted by the Ministry of Rural Development. Each of these surveys sought to represent distinct populations, and employed idiosyncratic sample designs and weighting schemes.

A detailed note covering key features of each sample frame is available for download.

Sampling deviation

Details will be made available after all rounds of data collection and analysis is complete.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The survey questionnaires covered the following subjects:

1. Agriculture: COVID-19-related changes in price realisation, acreage decisions, input expenditure, access to credit, access to fertilisers, etc.

2. Income and consumption: Changes in wage rates, employment duration, consumption expenditure, prices of essential commodities, status of food security etc.

3. Migration: Rates of in-migration, migrant income and employment status, return migration plans etc.

4. Access to relief: Access to in-kind, cash and workfare relief, quantities of relief received, and constraints on the access to relief.

5. Health: Access to health facilities and rates of foregone healthcare, knowledge of COVID-19 related symptoms and protective behaviours.

While a number of indicators were consistent across all three rounds, questions were added and removed as and when necessary to account for seasonal changes (i.e: in the agricultural cycle).

Cleaning operations

The India COVID-19 surveys were conducted using Computer Assisted Telephone Interview (CATI) techniques. The household questionnaire was implemented using the CATI software, SurveyCTO. The software was deployed through surveyors’ smartphones, who called respondents via mobile, and recorded their responses over the phone. If unreached, surveyors would attempt to call back respondents up to 7 times, often seeking explicit appointments for suitable times to avoid non-responses.

Validation and consistency checks were incorporated into the SurveyCTO software to avoid human error. Extreme values and outliers were scrutinised through a real time dashboard set up by IDinsight. Surveys were also audio audited by monitors to check for consistency and accuracy of question phrasing and answer recording. Finally, supervisors also randomly back-checked a subset of interviews to further ensure data accuracy.

IDinsight cleaned and labelled the data for further processing and analysis. The Development Data Lab examined the data for discrepancies and errors and merged the dataset with their proprietary spatial data.

All personally identifiable information has been removed from the datasets.

Response rate

Round 1: ~55% Round 2: ~46% Round 3: ~55%

This dataset is gleaned from employing a netnography methodology whereby Facebook posts and media content from London Latin American focused Facebook groups from 2021 backwards were extracted and analysed using Nvivo software. The posts were searched for their relevance to the Elephant and Castle mall in London, a hub from the Latin American community, and the effect of the closing of the hub on the wellbeing of the residences who posted about it. The study was to uncover wellbeing issues that effected displaced populations. The posts and videos were assessed and keywords systematically picked out for snowball analysis, regularity and presence within certain groups. This aided the identification of those factors most relevant to the wellbeing of these migrant groups. The dataset breaks down the number of mentions in individual posts (rather than the total mentions, where some posts may mention the same wellbeing factor more than once). It separates the wellbeing factors (lefthand column) against national groupings identified by the name of the individual Facebook group where the content of those posts originated.

This research directly addresses the 'Sustainability, equity, wellbeing and cultural connections' aspects identified in the call. It investigates through what processes forcibly displaced people become part of cities, in ways that sustainably contribute to economic development, cultural advancement and wellbeing. To this end, we will build a detailed understanding of the relations between placemaking processes, modalities of reception and wellbeing outcomes for displaced groups in Indian and European cities. We do this in a context of rapidly growing human displacement, forced migration and refugee flows to cities globally, and in European and Indian cities that are witnessing rising inequalities.

The research objectives, in approximate order of importance, are:

(i) Gain a deep understanding of the material and cultural production, design and architectural organisation of urban spaces of displacement and placemaking processes. (ii) Critically examine the ways in which these spaces and the displaced people in them are governed, through assemblages of actors and particular modalities of reception, to produce particular wellbeing effects. (iii) Assess in what ways and why displaced people negotiate access to these spaces. (iv) Develop, design and build strategic interventions that foster equity and inclusion in urban spaces, grounded in the wellbeing priorities of vulnerable displaced groups. (v) Build student and academic capacity for current and future cross- and trans-disciplinary research, design and learning relating to migration management in cities.

To achieve these objectives, the study is guided by an overarching research question: How to curate processes that foster displaced people to become part of the city, and to sustainably contribute to its economic development, socio-cultural cohesion and wellbeing? This question is broken down into four sub-questions:

1. Through what kinds of placemaking processes in physical and digital spaces do displaced people inhabit, build, make, give meaning and derive wellbeing?
2. In what ways and why do modalities of reception structure economic participation, socio-cultural cohesion and wellbeing outcomes for displaced people?
3. What is the role of urban informality, temporality and scale in placemaking processes and in the visions and functioning of modalities of reception?
4. What strategic architectural and policy interventions can advance equity and wellbeing for displaced communities in urban spaces? These questions, along with the wellbeing framework and the highly interdisciplinary methods that the study proposes, ensure that it addresses cross-cutting issues and themes highlighted by the study call, including urban inequalities, the (formal and informal) urban governance features, and practices that interact with vulnerable groups as they are engaged in placemaking processes to critically shape equity and wellbeing outcomes.

The project will convene European and Indian social science and humanities research communities to jointly conduct cross-country investigations into urban protracted displacement across lower-middle income (India) and higher income countries (Finland, Norway, UK). The comparative case study analysis across cities of various scales (from town to megacity) will advance new empirical, conceptual and theoretical insights.

This project also offers a unique approach to analysis and capacity building, making sure that the insights and skills gained amongst the consortium will last beyond the end of the project. We will systematically pair senior researchers and students from Architecture and Design studies and Social Sciences to advance a highly inter-disciplinary approach that has great potential to generate new insights and to advance architectural and policy solutions that address growing urban inequalities and economic development, and improve equity and socio-cultural wellbeing in a sustainable manner.

Census: Number of Migrants: Goa data was reported at 1,140,690.000 Person in 03-01-2011. This records an increase from the previous number of 785,020.000 Person for 03-01-2001. Census: Number of Migrants: Goa data is updated decadal, averaging 785,020.000 Person from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 1,140,690.000 Person in 03-01-2011 and a record low of 531,602.000 Person in 03-01-1991. Census: Number of Migrants: Goa data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAG001: Census of India: Migration: Number of Migrants: by States.

Census: Number of Migrants: Bihar data was reported at 27,244,869.000 Person in 03-01-2011. This records an increase from the previous number of 20,480,976.000 Person for 03-01-2001. Census: Number of Migrants: Bihar data is updated decadal, averaging 21,529,825.000 Person from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 27,244,869.000 Person in 03-01-2011 and a record low of 20,480,976.000 Person in 03-01-2001. Census: Number of Migrants: Bihar data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAG001: Census of India: Migration: Number of Migrants: by States.

Census: Number of Migrants: Chhattisgarh data was reported at 8,888,075.000 Person in 03-01-2011. This records an increase from the previous number of 6,907,199.000 Person for 03-01-2001. Census: Number of Migrants: Chhattisgarh data is updated decadal, averaging 7,897,637.000 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 8,888,075.000 Person in 03-01-2011 and a record low of 6,907,199.000 Person in 03-01-2001. Census: Number of Migrants: Chhattisgarh data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAG001: Census of India: Migration: Number of Migrants: by States.