As reported by a survey conducted in 2024 on digital news consumption, over 70 percent of respondents from India stated that they sourced their news online, which included social media, making it a popular form of accessing news. In comparison, 40 percent of respondents stated that they used print media as a news source during that period.

India Vital Statistics: Natural Growth Rate: per 1000 Population data was reported at 13.500 NA in 2020. This records a decrease from the previous number of 13.800 NA for 2019. India Vital Statistics: Natural Growth Rate: per 1000 Population data is updated yearly, averaging 18.500 NA from Dec 1970 (Median) to 2020, with 51 observations. The data reached an all-time high of 22.000 NA in 1971 and a record low of 13.500 NA in 2020. India Vital Statistics: Natural Growth Rate: per 1000 Population data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under Global Database’s India – Table IN.GAH001: Vital Statistics.

As of February 2025, there were 153 data centers in India. Mumbai, with its 38 data centers, led the market. It was followed by Bengaluru, with 21 data centers. During the same period, the United States leads the world with more than five thousand data centers.

As of 2023, the average data consumption per user per month in India was at **** gigabytes. 4G data traffic contributes to ** percent of the overall data traffic while 5G was launched in India in October 2022. Increased online education, remote working for professionals and higher OTT viewership contributed to the data traffic growth.

General Expenditure comprising of Defence, Police, External Affairs, Food Subsidy, Development Expenditure comprising of Railways, Posts and Telecommunications, Social and Community Services, General Economic Services, Agricultural and allied services, and Loans and Advances of the Centre and the States

The dataset was created as part of an ESRC-sponsored study, ‘British economic, social, and cultural interactions with Asia, 1760-1833’. It contains statistics relating to the trade and domestic finances of the monopolistic English East India Company primarily between 1755 and 1834, the year in which the Company ceased to function as a commercial organization. Until now quantitative data derived from original sources has only been available in time series for the Company’s trade and some aspects of its domestic finances for the years before 1760. But many of the details, patterns, and trends of trade and finance in the decades after 1760, a most important period when the Company fully embarked on the interlinked processes of military, political, and commercial expansion in Asia, have remained unclear. In creating this dataset, the aim was thus two-fold: i) to establish for the first time a set of statistics detailing the changing value, volume, and geographical structure of the East India Company’s overseas trade for the period when the Company began to exert imperial control over large parts of the Indian subcontinent; and ii) to generate select statistics relating to the Company’s domestic finances, thereby enabling analysis to be undertaken of a range of Company interactions with Britain’s economy and society.

Post Statistics: Number of Post Office: Madhya Pradesh data was reported at 8,286.000 Unit in 2016. This records a decrease from the previous number of 8,323.000 Unit for 2015. Post Statistics: Number of Post Office: Madhya Pradesh data is updated yearly, averaging 8,316.500 Unit from Mar 2009 to 2016, with 8 observations. The data reached an all-time high of 11,444.000 Unit in 2009 and a record low of 8,286.000 Unit in 2016. Post Statistics: Number of Post Office: Madhya Pradesh data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TE001: Post Statistics.

Looking back 45 years or so, progress against poverty in India has been highly uneven over time and space. It took 20 years for the national poverty rate to fall below—and stay below—its value in the early 1950s. And trend rates of poverty reduction have differed appreciably between states. This research project aimed to understand what influence economy-wide and sectoral factors have played in the evolution of poverty measures for India since the 1950s, and to draw lessons for the future. This database contains detailed statistics on a wide range of topics in India. The data are presented at the state level and at the all-India level separately. The database uses published information to construct comprehensive series in six subject blocks. Period coverage is roughly from 1950 to 1994. The database contains 30 spreadsheets and 89 text files (ASCII) that are grouped into the six subject blocks. The formats and sizes of the 30 spreadsheets vary considerably. The list of variables included: . Expenditures (distribution) . National Accounts . Prices Wages . Population . Rainfall

India IT Industry Revenue: USD: Domestic data was reported at 41.000 USD bn in 2019. This stayed constant from the previous number of 41.000 USD bn for 2018. India IT Industry Revenue: USD: Domestic data is updated yearly, averaging 20.380 USD bn from Mar 1997 (Median) to 2019, with 23 observations. The data reached an all-time high of 48.000 USD bn in 2015 and a record low of 2.661 USD bn in 1997. India IT Industry Revenue: USD: Domestic data remains active status in CEIC and is reported by National Association of Software and Service Companies. The data is categorized under Global Database’s India – Table IN.TF007: Information Technology Statistics: National Association of Software and Service Company: IT-BPM: Domestic Revenue.

While Indians between 12 and 34 years dominated internet use from 2013 to 2019 with about 65 percent of the total market, this was projected to change by 2025. Between 2019 and 2025, it was estimated that age group 35 years and older would make up ** percent of internet usage in India. Gender and internet Among the total internet users in the country, it was found that only about ** percent were female users. While this was expected to change to ** percent male users and ** percent female users by 2020, it still showed a gender gap in internet accessibility in the south-Asian country. While several factors lead to this digital gender gap, economic and socio-cultural barriers stand out as the most compelling reasons. Older Indians part of digitalization The median age of India’s population was around 27 years in 2015, echoing the range of the country’s majority internet user base. The estimated shift, however, in the years to come would be the successful efforts towards digitalizing India. If done right, this would propel older adults to adopt and master new media technologies in their daily activities beyond social media and communication, including the use of financial services.

The dataset contains All India Yearly Balance Of Payments in India BPM 6 from Handbook of Statistics on Indian Economy.

Note: 1. Data for 2023-24 are preliminary estimates and 2022-23 are partially revised. 2. Total may not tally due to rounding off.

The data shows the year-wise all India level statistics related to mental hospitals in the years between 2000 an 2004.

Note: 1. Figures in brackets in Number of Mental Hospitals indicate the number of reporting hospitals. 2. All India/State-wise data for 2005 and onwards are not available. 3. Data for 2003 and 2004 is provisional. 4. 2002 data for number of beds available, patients admitted, patients discharged during the year and patients died during the year.

The dataset contains All India Yearly Outstanding Non-Resident Indian (NRI) Deposits from Handbook of Statistics on Indian Economy.

Note: 1. The figures are outstanding as on last Friday of March. 2. The figures on NRI deposits are as reported by scheduled commercial banks in India.

There were 121 200 000 Linkedin users in India in January 2024, which accounted for 8.3% of its entire population. People aged 25 to 34 were the largest user group (61 000 000).

Revenue Deficits of the Centre, States, Centre and States combined and as percentages of respective GDPs

Consumer Spending in India decreased to 27200.39 INR Billion in the first quarter of 2025 from 28433.68 INR Billion in the fourth quarter of 2024. This dataset provides - India Consumer Spending - actual values, historical data, forecast, chart, statistics, economic calendar and news.

There were 392 465 000 Instagram users in India in June 2024, which accounted for 26.7% of its entire population. The majority of them were men - 66.9%. People aged 18 to 24 were the largest user group (172 600 000). The highest difference between men and women occurs within people aged 25 to 34, where men lead by 99 300 000.

The dataset contains All India Yearly External Debt from Handbook of Statistics on Indian Economy. IDBs : India Development Bonds FCCBs : Foreign Currency Convertible Bonds IFC(W) : International Finance Corporation (Washington) FC(B&O) : Foreign Currency (Banks & Others) Deposits

Note: 1. Other concessional multilateral Government borrowing refers to debt outstanding to Institutions like IFAD, OPEC & EEC (SAC). 2. Multilateral non-concessional Government/ public sector/ financial institutions other borrowings refers to debt outstanding against loans from ADB. 3. Securitised commercial borrowings (inclu. IDBs and FCCBs) includes net Investment by 100% Fll debt funds, Resurgent India Bonds (RIBs) and India Millenium Deposits(IMDs). 4. Rupee debt refers to debt owed to Russia denominated in Rupees and converted at current exchange rates, payable in exports. 5. Civillian's rupee debt includes Supplier’s credit from end-March 1990 onwards. 6. Short-term debt does not include suppliers’ credit of up to 180 days from 1994 till 2004. 7. Multilateral loans do not include revaluation of IBRD pooled loans and exchange rate adjustment under IDA loans for Pre-1971 credits. 8. Debt- service ratio from the year 1992 - 93 includes the revised private transfer contra-entry on account of gold and silver imports.

India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data was reported at 26.700 NA in 2016. This records a decrease from the previous number of 26.800 NA for 2015. India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data is updated yearly, averaging 27.100 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 29.700 NA in 2000 and a record low of 26.700 NA in 2016. India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data was reported at 19.800 NA in 2016. This records a decrease from the previous number of 20.000 NA for 2015. India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data is updated yearly, averaging 21.200 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 23.400 NA in 2000 and a record low of 19.800 NA in 2016. India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;