Context

This is dataset of West Bengal candidates for ongoing 2021 Assembly election. I scraped the dataset from https://myneta.info/ . You can find the script I used for scraping by visiting github.

Content

This dataset contains information about candidates from 91 constituencies of West Bengal. Candidates name, constituency, party, criminal cases on candidates, education of candidate , total assets and liabilities owned by the candidate.

Acknowledgements

Thank you to Myneta.info for doing great work.

This point dataset shows village locations with socio-demographic and economic Census data for 1991 for the State of West Bengal, India linked to the 1991 Census. Includes village socio-demographic and economic Census attribute data such as total population, population by sex, household, literacy and illiteracy rates, and employment by industry. This layer is part of the VillageMap dataset which includes socio-demographic and economic Census data for 1991 at the village level for all the states of India. This data layer is sourced from secondary government sources, chiefly Survey of India, Census of India, Election Commission, etc. This map includes data for 40848 villages, 401 towns, 18 districts, and 1 state.

The dataset contains details of tiger population estimation pertaining to tiger landscapes in the country

Note: 1. States have been categorised as Shivalik-Gangetic Plain Landscape Complex, Uttarakhand, Uttar Pradesh, Bihar. Shivalik-Gangetic includes: Central India Landscape Complex, Andhra Pradesh (Including Telangana), Chhattisgarh, Madhya Pradesh, Maharashtra, Odisha, Rajasthan, Jharkhand, Central Indian, Western Ghats Landscape Complex, Karnataka, Kerala, Tamil Nadu, Goa. Western Ghats includes: North East Hills and Brahmaputra Flood Plains, Assam, Arunachal Pradesh, Mizoram, Northern West Bengal, North East Hills and Brahmaputra includes Sundarbans. NB: Ranipur (Uttar Pradesh) is added in Shivalik landscape for convenience.

1. State population estimate does not add up to the landscape estimate due to common tigers, tiger outside protected areas, and model range limits.

Social media platforms have become integral tools in the conduct of foreign policy for many nations, including India. This dataset serves as a resource for analyzing ‘Social Media and India’s Foreign Policy: The Case Study of ‘X’ Diplomacy during the Covid-19 Pandemic.’ The data were collected through a web-based questionnaire distributed primarily to people aged 18 – 61 and above in India. A total of 171 valid data were collected from 17 states offering extensive geographic coverage and stored in Mendeley. The 15 contributor states are Goa, Maharashtra, Tamil Nadu, Gujarat, Delhi, Assam, Haryana, Jammu and Kashmir, Karnataka, Kerala, Punjab, Rajasthan, Tripura, Uttar Pradesh and West Bengal. It encompasses diverse question formats, including single-choice, multiple-choice, quizzes, and open-ended. The study underscores the opportunities and challenges of employing 'X' diplomacy in India's foreign policy. Thus, there were two hypotheses. First, India's effective use of 'X' diplomacy positively impacts public perception of India's foreign policy effectiveness. Second, India's adept use of 'X' diplomacy during the COVID-19 pandemic enhances its ability to manage and respond to the crisis effectively. This data shows public perception of the effective use of social media by the Government of India, particularly in the crisis situation. Data also highlight the significant change in India’s narrative through its ‘X’ diplomacy, effectively setting the narratives, public perceptions, and diplomatic strategies. This data can be fully utilized in the study of the significance of social media in India’s foreign policy, the role of social media like ‘X’ in the making of India’s foreign policy, how effective social media like ‘X’ was during the Covid-19 pandemic and how Indian government utilized social media like ‘X’ to delivered messages and to set the narrative in the international politics.

Context

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

Content

• india-districts-census-2011.csv - Population enumeration data with expanded columns.
• india_census_housing-hlpca-full.csv - Housing statistics for total (rural + urban) population by district.
• gdp_AndhraPradesh1.csv , gdp_AndhraPradesh2 : Contains GDP data for state AP.
• gdp_ArunachalPradesh.csv: Contains GDP data for state ArunachalPradesh.
• gdp_Assam1.csv, gdp_Assam2.csv : Contains GDP data for state Assam.
• gdp_Bihar1.csv , gdp_Bihar2.csv : Contains GDP data for state Bihar.
• gdp_Chattisgarh.csv : Contains GDP data for state Chattisgarh.
• gdp_Haryana.csv : Contains GDP data for state Haryana.
• gdp_HimachalPradesh.csv : Contains GDP data for state HimachalPradesh.
• gdp_Jharkhand.csv : Contains GDP data for state Jharkhand.
• gdp_Karnataka1.csv , gdp_Karnataka2.csv : Contains GDP data for state Karnataka.
• gdp_Kerala1.csv , gdp_Kerala2.csv : Contains GDP data for state Kerala.
• gdp_MadhyaPradesh.csv : Contains GDP data for state MadhyaPradesh.
• gdp_Maharashtra1.csv , gdp_Maharashtra2.csv : Contains GDP data for state Maharashtra.
• gdp_Manipur.csv : Contains GDP data for state Manipur.
• gdp_Meghalaya.csv : Contains GDP data for state Meghalaya.
• gdp_Mizoram.csv : Contains GDP data for state Mizoram.
• gdp_Odisha1.csv , gdp_Odisha2.csv : Contains GDP data for state Odhisha.
• gdp_Punjab1.csv , gdp_Punjab2.csv : Contains GDP data for state Punjab.
• gdp_Rajasthan1.csv , gdp_Rajasthan2.csv : Contains GDP data for state Rajasthan.
• gdp_Sikkim.csv : Contains GDP data for state Sikkim.
• gdp_Tamilnadu.csv : Contains GDP data for state Tamilnadu.
• gdp_Uttarakhand.csv : Contains GDP data for state Uttarakhand.
• gdp_UttarPradesh1.csv , gdp_UttarPradesh2.csv : Contains GDP data for state UttarPradesh.
• gdp_WestBengal1.csv , gdp_WestBengal2.csv : Contains GDP data for state West Bengal.

Acknowledgements

https://www.kaggle.com/danofer/india-census

https://www.kaggle.com/umeshnarayanappa/explore-census-2001-india

http://udise.in/drc.htm

https://data.gov.in/catalog/district-wise-gdp-and-growth-rate-current-price2004-05

https://data.gov.in/catalog/district-wise-gdp-and-growth-rate-constant-price1999-2000

Banner photo by @ishant_mishra54 from Unsplash.

Inspiration

What are the socioeconomic trends in different parts of India?

This dataset provides structured information on all 294 constituencies of the West Bengal Legislative Assembly as per the 2021 election data. Each entry includes the constituency name, reservation category (if any), district, corresponding Lok Sabha constituency, and the total number of registered electors.

The dataset was compiled from the Wikipedia page on West Bengal Assembly Constituencies using the Wikipedia API (accessed October 2025). Minor formatting adjustments were made to ensure clean CSV structure and consistent field names.

Map Attribution: Map of West Bengal Assembly constituencies by Furfur — sourced from the [Election Commission of India]. Licensed under Creative Commons Attribution–ShareAlike 3.0 Unported (CC BY-SA 3.0)

Inspiration

• Explore how constituencies are distributed across districts.
• Analyze voter population variation by reservation type.
• Create visualizations to map constituencies geographically.
• Integrate with socio-economic or demographic datasets for deeper insights.

Acknowledgment

Data sourced from Wikipedia contributors under the Creative Commons Attribution–ShareAlike 4.0 International License (CC BY-SA 4.0). This dataset is shared for educational and analytical purposes.

Introduction

Welcome to the Bengali Scripted Monologue Speech Dataset for the Retail & E-commerce domain. This dataset is built to accelerate the development of Bengali language speech technologies especially for use in retail-focused automatic speech recognition (ASR), natural language processing (NLP), voicebots, and conversational AI applications.

Speech Data

This training dataset includes 6,000+ high-quality scripted audio recordings in Bengali, created to reflect real-world scenarios in the Retail & E-commerce sector. These prompts are tailored to improve the accuracy and robustness of customer-facing speech technologies.

Topic Diversity

This dataset includes a comprehensive set of retail-specific topics to ensure wide linguistic coverage for AI training:

Contextual Enrichment

To increase training utility, prompts include contextual data such as:

These additions help your models learn to recognize structured and unstructured retail-related speech.

Transcription

Every audio file is paired with a verbatim transcription, ensuring consistency and alignment for model training.

Metadata

Detailed metadata is included to support filtering, analysis, and model evaluation:

Introduction

The Bengali Wake Word & Voice Command Dataset is expertly curated to support the training and development of voice-activated systems. This dataset includes a large collection of wake words and command phrases, essential for enabling seamless user interaction with voice assistants and other speech-enabled technologies. It’s designed to ensure accurate wake word detection and voice command recognition, enhancing overall system performance and user experience.

Speech Data

This dataset includes 20,000+ audio recordings of wake words and command phrases. Each participant contributed 400 recordings, captured under varied environmental conditions and speaking speeds. The data covers:

Participant Diversity

Recording Details

Dataset Diversity

This diversity ensures robust training for real-world voice assistant applications.

Metadata

Each audio file is accompanied by detailed metadata to support advanced filtering and training needs.

Use Cases & Applications

Introduction

This Bengali Call Center Speech Dataset for the Retail and E-commerce industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for Bengali speakers. Featuring over 30 hours of real-world, unscripted audio, it provides authentic human-to-human customer service conversations vital for training robust ASR models.

Curated by FutureBeeAI, this dataset empowers voice AI developers, data scientists, and language model researchers to build high-accuracy, production-ready models across retail-focused use cases.

Speech Data

The dataset contains 30 hours of dual-channel call center recordings between native Bengali speakers. Captured in realistic scenarios, these conversations span diverse retail topics from product inquiries to order cancellations, providing a wide context range for model training and testing.

Topic Diversity

This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral, ensuring real-world scenario coverage.

Such variety enhances your model’s ability to generalize across retail-specific voice interactions.

Transcription

All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.

These transcriptions are production-ready, making model training faster and more accurate.

Metadata

Rich metadata is available for each participant and conversation:

This granularity supports advanced analytics, dialect filtering, and fine-tuned model evaluation.

Usage and Applications

This dataset is ideal for a range of voice AI and NLP applications:

Context

Census of India is a rich database which can tell stories of over a billion Indians. It is important not only for research point of view, but commercially as well for the organizations that want to understand India's complex yet strongly knitted heterogeneity. However, nowhere on the web, there exists a single database that combines the district- wise information of all the variables (most include no more than 4-5 out of over 50 variables!). Extracting and using data from Census of India 2001 is quite a laborious task since all data is made available in scattered PDFs district wise. Individual PDFs can be extracted from http://www.censusindia.gov.in/(S(ogvuk1y2e5sueoyc5eyc0g55))/Tables_Published/Basic_Data_Sheet.aspx.

Content

This database has been extracted from Census of 2001 and includes data of 590 districts, having around 80 variables each.

In case of confusion regarding the context of the variable, refer to the following PDF and you will be able to make sense out of it: http://censusindia.gov.in/Dist_File/datasheet-2923.pdf

All the extraction work can be found @ https://github.com/preetskhalsa97/census2001auto The final CSV can be found at finalCSV/all.csv

The subtle hack that was used to automate extraction to a great extent was the the URLs of all the PDFs were same except the four digits (that were respective state and district codes).

A few abbreviations used for states:

AN- Andaman and Nicobar CG- Chhattisgarh D_D- Daman and Diu D_N_H- Dadra and Nagar Haveli JK- Jammu and Kashmir MP- Madhya Pradesh TN- Tamil Nadu UP- Uttar Pradesh WB- West Bengal

A few variables for clarification: Growth..1991...2001- population growth from 1991 to 2001 X0..4 years- People in age group 0 to 4 years SC1- Scheduled Class with highest population

Acknowledgements

Inspiration

This is a massive dataset which can be used to explain the interplay between education, caste, development, gender and much more. It really can explain a lot about India and propel data driven research. Happy Number Crunching!

The data shows the statistics of different item-wise reports on a cumulative yearly basis in states up to the sub-district level in West Bengal. It included 1) Ante Natal Care (ANC) - Antenatal care (ANC) is a means to identify high-risk pregnancies and educate women so that they might experience healthier delivery and outcomes. 2) Deliveries - The delivery of the baby by the pregnant women 3) Number of Caesarean (C-Section) deliveries - Caesarean delivery (C-section) is used to deliver a baby through surgical incisions made in the abdomen and uterus. 4) Pregnancy outcome & details of new-born - The records kept of the pregnancy outcome along with the details of new-born 5) Complicated Pregnancies - The different pregnancies that were not normal and had complications 6) Post Natal Care (PNC) - Postnatal care is defined as care given to the mother and her new-born baby immediately after the birth of the placenta and for the first six weeks of life 7) Reproductive Tract Infections/Sexually Transmitted Infections (RTI/STI) Cases - The records of reproductive tract infections along with the records of the sexually transmitted cases 8) Family Planning - The different methods used by families to keep track of family 9) CHILD IMMUNISATION - The records of child immunisation which are records of vaccination 10) Number of cases of Childhood Diseases (0-5 years) - The records of the number of cases of childhood diseases within the age of 5 years old 11) NVBDCP - The National Vector Borne Disease Control Programme (NVBDCP) is one of the most comprehensive and multi-faceted public health activities in the country and concerned with the prevention and control of vector-borne diseases, namely Malaria, Filariasis, Kala-azar, Dengue and Japanese Encephalitis (JE). 12) Adolescent Health - The record of the conditions of adolescent health 13 ) Directly Observed Treatment, Short-course (DOTS) - Directly observed treatment, short-course (DOTS, also known as TB-DOTS) is the name given to the tuberculosis (TB) control strategy recommended by the World Health Organization 14) Patient Services - Patient Services means those which vary with the number of personnel; professional and para-professional skills of the personnel; specialised equipment, and reflect the intensity of the medical and psycho-social needs of the patients. 15) Laboratory Testing - A medical procedure that involves testing a sample of blood, urine, or other substance from the body. Laboratory tests can help determine a diagnosis, plan treatment, check if the treatment works, or monitor the disease over time. 16) Details of deaths reported with probable causes - The reports of deaths recorded with possible reasons are given in a detail 17) Vaccines - The reports of vaccines which are recorded 18) Syringes - It is the number of syringes that are used and recorded 19) Rashtriya Bal Swasthaya Karyakram (RBSK) - Rashtriya Bal Swasthya Karyakram (RBSK) is an important initiative aiming at early identification and early intervention for children from birth to 18 years to cover 4 'D's viz. Defects at birth, Deficiencies, Diseases, Development delays, including disability. 20) Coverage under WIFS JUNIOR - The coverage of the Weekly Iron Folic Acid Supplementation Programme for children six to one 21) Maternal Death Reviews (MDR) - A maternal death review is cross-checking how the mother died. It provides a rare opportunity for a group of health staff and community members to learn from a tragic – and often preventable. 22) Janani Shishu Suraksha Karyakaram (JSSK)- This initiative provides free and cashless services to pregnant women, including normal deliveries and caesarean operations. It entitles all pregnant women in public health institutions to free and no-expense delivery, including caesarean section.

Introduction

This Bengali Call Center Speech Dataset for the Delivery and Logistics industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for Bengali-speaking customers. With over 30 hours of real-world, unscripted call center audio, this dataset captures authentic delivery-related conversations essential for training high-performance ASR models.

Curated by FutureBeeAI, this dataset empowers AI teams, logistics tech providers, and NLP researchers to build accurate, production-ready models for customer support automation in delivery and logistics.

Speech Data

The dataset contains 30 hours of dual-channel call center recordings between native Bengali speakers. Captured across various delivery and logistics service scenarios, these conversations cover everything from order tracking to missed delivery resolutions offering a rich, real-world training base for AI models.

Topic Diversity

This speech corpus includes both inbound and outbound delivery-related conversations, covering varied outcomes (positive, negative, neutral) to train adaptable voice models.

This comprehensive coverage reflects real-world logistics workflows, helping voice AI systems interpret context and intent with precision.

Transcription

All recordings come with high-quality, human-generated verbatim transcriptions in JSON format.

These transcriptions support fast, reliable model development for Bengali voice AI applications in the delivery sector.

Metadata

Detailed metadata is included for each participant and conversation:

This metadata aids in training specialized models, filtering demographics, and running advanced analytics.

Usage and Applications

This

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.