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The American Rescue Plan Act established the Restaurant Revitalization Fund (RRF) to provide funding to help restaurants and other eligible businesses keep their doors open. This program provided restaurants with funding equal to their pandemic-related revenue loss up to $10 million per business and no more than $5 million per physical location. Recipients are not required to repay the funding as long as funds are used for eligible uses no later than March 11, 2023.
This dataset details New York State recipients of RRF funds, including the loan number, approval date, business name, address, city, state, zip code, grant amount, franchise name (if applicable), rural/urban indicator, HUBZone indicator, Congressional District (CD), and indicators of whether the grant was used for outdoor seating, a covered supplier expense, debt relief or refinancing, food expenses related to on-site consumption or delivery/catering services ,indoor maintenance expenses such as rent or mortgage payments ,or operations expenditures such as employee salaries
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
- Identify restaurant trends during the COVID-19 pandemic.
- Identify areas of the country that have been most affected by the pandemic.
- Which businesses are most likely to receive funding from the government
If you use this dataset in your research, please credit the original authors.
License
See the dataset description for more information.
File: us-sba-covid-19-relief-to-nys-business-restaurant-revitalization-fund-1.csv | Column name | Description | |:-------------------------------------|:-----------------------------------------------------------------------------------| | LoanNumber | The loan number for the recipient. (Integer) | | ApprovalDate_Year | The year the loan was approved. (Integer) | | ApprovalDate_Month | The month the loan was approved. (Integer) | | ApprovalDate_Day | The day the loan was approved. (Integer) | | BusinessName | The name of the business that received the loan. (String) | | BusinessAddress | The address of the business that received the loan. (String) | | BusinessCity | The city of the business that received the loan. (String) | | BusinessState | The state of the business that received the loan. (String) | | BusinessZip | The zip code of the business that received the loan. (String) | | GrantAmount | The amount of the grant received by the business. (Float) | | FranchiseName | The name of the franchise, if applicable. (String) | | RuralUrbanIndicator | An indicator of whether the business is located in a rural or urban area. (String) | | HubzoneIndicator | An indicator of whether the business is located in a HUBZone. (String) | | CD | The congressional district in which the business is located. (String) | | grant_purp_cons_outdoor_seating | An indicator of whether the grant was used for outdoor seating. (String) | | grant_purpose_covered_supplier | An indicator of whether the grant was used for a covered supplier. (String) | | grant_purpose_debt | An indicator of whether the grant was used for debt relief. (String) | | grant_purpose_food | An indicator of whether the grant was used for food purposes. (String) | | grant_purpose_maintenance_indoor | An indicator of whether the grant was used for indoor maintenance. (String) | | grant_purpose_operations | An indicator of whether the grant was used for operations. (String) |
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TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This data set contains information collected as part of the three editions of the City of Montreal's participatory budgeting. The data presents the results collected for each edition at each phase of the process, from the collection of ideas, to the citizen vote. For the first edition of the participatory budget (BP1), the City first devoted $10 million from its 2020-2022 investment budget. The total budget allocated to projects was increased by $15 million, from $10 million to $25 million. The additional amount made it possible to finance 5 additional projects. For the second (BP2) third (BP3) editions, it has respectively reserved $31.5 million from its 2023-2032 10-year capital program and $45 million in the 2024-2033 10-year capital program. These amounts aim to carry out projects resulting from citizen proposals and chosen by the population. Among these amounts, for the last two editions, at least $10 million will be dedicated to projects proposed BY young people and their families (“youth seal”) or designed FOR young people, in connection with the youth theme.
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TwitterThis data set contains information collected as part of the three editions of the City of Montreal's participatory budgeting. The data presents the results collected for each edition at each phase of the process, from the collection of ideas, to the citizen vote. For the first edition of the participatory budget (BP1), the City first devoted $10 million from its 2020-2022 investment budget. The total budget allocated to projects was increased by $15 million, from $10 million to $25 million. The additional amount made it possible to finance 5 additional projects. For the second (BP2) third (BP3) editions, it has respectively reserved $31.5 million from its 2023-2032 10-year capital program and $45 million in the 2024-2033 10-year capital program. These amounts aim to carry out projects resulting from citizen proposals and chosen by the population. Among these amounts, for the last two editions, at least $10 million will be dedicated to projects proposed BY young people and their families (“youth seal”) or designed FOR young people, in connection with the youth theme.
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
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Bitcoin ETFs and the “Sell-the-News” Phenomenon CryptoQuant, a renowned analytics firm, noted that the market anticipates a 90% likelihood of spot Bitcoin ETF approvals by early January. This optimism, reflected in 32 meetings between ETF issuers and the US Securities and Exchange Commission (SEC), suggests constructive dialogue. However, it also sets the stage for a classic “sell-the-news” event.
The recent announcement from Blackrock about seeding its ETF with $10 million is a bullish sign. Nonetheless, CryptoQuant highlighted the impact of miner behavior. With the recent surge in Bitcoin prices, miners are experiencing high unrealized profits and have started increasing their selling activities, which could contribute to downward pressure.
The bitcoin (BTC) price started 2024 on a roll, adding more than 7% in 24 hours to approach $46,000, the highest level since April 2022, in a strong start to the new year. As has been the case for the past several weeks, anticipation that the U.S. Securities and Exchange Commission (SEC) will greenlight a number of spot bitcoin ETFs appears to be the catalyst for the move higher. A Reuters report over the weekend suggested the regulatory agency could begin notifying ETF sponsors as soon as Tuesday that their applications were to be approved. Traditional-finance heavyweights such as BlackRock and VanEck are among the 13 companies in the race – and the move could fuel buying pressure for bitcoin in the coming months as the first regulated spot bitcoin product in the U.S., traders expect. Still, market commentators and analysts remain mixed on the impact of ETF approval. "Some analysts from cryptocurrency trading platforms believe that even if the ETF is approved, Bitcoin may not immediately experience a significant rally," Ryan Lee, chief analyst at Bitget Research, said in an email. "There are also some optimistic views, such as influential trader Scott Melker predicting that Bitcoin could surge to $54,000 in the next few days once the SEC approves the ETF. Matrixport predicts that BTC will rise to $50,000 within a month after passing the BTC spot ETF in January." Bitcoin burst through $45,000 and was trading recently at $45,707, according to CoinDesk Indices data. Meanwhile, broader crypto markets are on the move higher as well, with ether (ETH) ahead by 4% and solana (SOL) and avalanche (AVAX) up as much as 12%.
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TwitterThe data represents the percent change in wages for an individual who has wages recorded in the Unemployment Compensation (UC) wage record file in the quarter in which they completed Industry Partnership training and wages found in the UC wage record file for that individual four quarters later. The change could be an increase or a decrease in wages. For example, if an individual completed training in the third quarter of 2013 and earned $5,000 in that quarter and earned $7,500 in the third quarter of 2014 the percent change for that individual would be 50%. The file incudes a count of all individuals who benefited from industry partnership training, the workforce development area of the industry partnership, the training program completed and the percentage change in wages per individual training. The top line of the file includes the overall percentage change for all trainings.
*The goal for Labor & Industry is based on receiving $10 million to fund Industry Partnerships.
This dataset is for Program Year 2013-2017 and will be updated annually due to federal release schedule. There are many reasons why an individual’s wage may have changed dramatically. Some of the reasons for negative wage changes or large increases in wages are listed below (not an exhaustive list). • An individual may have left the job, was laid off, or retired within the year after they were trained. • An individual may have become ill and left work. • An individual may have accepted a job in or moved to another state. • An individual may have been working two jobs and switched to one, or vice versa. • An individual’s hours may have been reduced/increased during a quarter. • Overtime hours may have been reduced/increased during a quarter. • An individual may have taken family leave. • A bonus could have been paid right after training was completed. • Wage records may not have been reported. • An employer may have closed and laid off all of their employees.
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TwitterThe International, often abbreviated as TI, is an annual tournament organized by Valve. In 2015 Valve increased their number of hosted events, founding the Dota Major Championships which incorporates The International into its structure. The International remains the biggest and most prestigious event on the Major Championship circuit.
The first International was held in Cologne, Germany, during the trade show Gamescom, in order to unveil Dota 2 to worldwide audiences. It drew attention due to its staggering $1.6 million USD prize pool (with $1 million for the champion). 16 teams were invited to play for the title.
In 2012 The International moved to Seattle, Washington. The prize pool remained at $1.6 million USD. Only 14 teams were invited; two additional slots were awarded to the winners of regional qualifiers.
Since 2013, the Dota 2 community has been able to contribute to the prize pool. The total prize of The International 2013 grew to $2.8 million USD. The prize pool surpassed $10 million in 2014 and $20 million in 2016.
In 2018, after six years in Seattle, The International was held in Vancouver, Canada. In 2019, The International was held in Shanghai, China, the prize pool surpassed $34 million, making it the largest prize pool for any single esports tournament until it was surpassed by The International 2020.
The International 10 was originally scheduled to take place in Stockholm, Sweden in 2020, but was delayed to 2021 due to the COVID-19 pandemic. In 2021, the event was relocated to take place in Bucharest, Romania due to potential problems with COVID-19 related restrictions in Sweden.
A compiled dataset contains prize pool, participated teams and team rosters data for every The International Championship 2011-2021.
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TwitterBy State of New York [source]
The American Rescue Plan Act established the Restaurant Revitalization Fund (RRF) to provide funding to help restaurants and other eligible businesses keep their doors open. This program provided restaurants with funding equal to their pandemic-related revenue loss up to $10 million per business and no more than $5 million per physical location. Recipients are not required to repay the funding as long as funds are used for eligible uses no later than March 11, 2023.
This dataset details New York State recipients of RRF funds, including the loan number, approval date, business name, address, city, state, zip code, grant amount, franchise name (if applicable), rural/urban indicator, HUBZone indicator, Congressional District (CD), and indicators of whether the grant was used for outdoor seating, a covered supplier expense, debt relief or refinancing, food expenses related to on-site consumption or delivery/catering services ,indoor maintenance expenses such as rent or mortgage payments ,or operations expenditures such as employee salaries
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
- Identify restaurant trends during the COVID-19 pandemic.
- Identify areas of the country that have been most affected by the pandemic.
- Which businesses are most likely to receive funding from the government
If you use this dataset in your research, please credit the original authors.
License
See the dataset description for more information.
File: us-sba-covid-19-relief-to-nys-business-restaurant-revitalization-fund-1.csv | Column name | Description | |:-------------------------------------|:-----------------------------------------------------------------------------------| | LoanNumber | The loan number for the recipient. (Integer) | | ApprovalDate_Year | The year the loan was approved. (Integer) | | ApprovalDate_Month | The month the loan was approved. (Integer) | | ApprovalDate_Day | The day the loan was approved. (Integer) | | BusinessName | The name of the business that received the loan. (String) | | BusinessAddress | The address of the business that received the loan. (String) | | BusinessCity | The city of the business that received the loan. (String) | | BusinessState | The state of the business that received the loan. (String) | | BusinessZip | The zip code of the business that received the loan. (String) | | GrantAmount | The amount of the grant received by the business. (Float) | | FranchiseName | The name of the franchise, if applicable. (String) | | RuralUrbanIndicator | An indicator of whether the business is located in a rural or urban area. (String) | | HubzoneIndicator | An indicator of whether the business is located in a HUBZone. (String) | | CD | The congressional district in which the business is located. (String) | | grant_purp_cons_outdoor_seating | An indicator of whether the grant was used for outdoor seating. (String) | | grant_purpose_covered_supplier | An indicator of whether the grant was used for a covered supplier. (String) | | grant_purpose_debt | An indicator of whether the grant was used for debt relief. (String) | | grant_purpose_food | An indicator of whether the grant was used for food purposes. (String) | | grant_purpose_maintenance_indoor | An indicator of whether the grant was used for indoor maintenance. (String) | | grant_purpose_operations | An indicator of whether the grant was used for operations. (String) |