As of February 1, 2025, the end of the 2024 financial year, Target had a total of 1,978 stores open throughout the United States. This was an increase of 22 from a year earlier. Target Corporation operates a chain of general merchandise stores, which offer a wide variety of general merchandise and food products to their customers. The company has operated primarily in the United States since its inception. Target Corporation is one of the most valuable retail brands in the world. The development of an American retail giant The company started out as the Dayton Dry Goods Company in 1902, later changing its name to the Dayton Company, but more commonly known as Dayton’s. The company was run under the Dayton-Hudson Corporation banner up until the year 2000, when it was renamed Target Corporation. The company spread across the United States and even entered the Canadian market for a brief period, but all of the company’s Canadian stores were closed in 2015. In financial year 2024, Target had revenues amounting to approximately 106.6 billion U.S. dollars, making it one of the leading American retailers. What does Target sell? Target Corporation sells a wide range of goods, such as food, apparel, household essentials, and seasonal offerings, as well as many others. As of 2024, the majority of sales came from the food and beverage segment. The company also sells products online, through target.com. In 2024, the share of Target's online sales amounted to almost 20 percent.

The latest numerical data of rainwater storage-related sensing equipment collected by IoW (Internet of Water Resources) mainly collects sensing values such as rainwater inflow, rainwater outflow, and tap water replenishment cumulative flow.

Latest FoodData Central data from U.S. Department of Agriculture.

View data type documentation for each of FoodData Central's data types.

View Download Field Descriptions (PDF - 300K) for definitions of all the terms and labels used in the download files of FoodData Central. This guide is also included in dataset.

Analysis of ‘Covid-19 Weekly Trends In Europe - Latest Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/anandhuh/covid19-weekly-trends-in-europe-latest-data on 28 January 2022.

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

Content

This dataset contains data of weekly trend of Covid-19 in Europe (January 01 - January 07, 2022)

Attribute Information

1. Country/Other
2. Cases in the last 7 days
3. Cases in the preceding 7 days
4. Weekly Case % Change
5. Cases in the last 7 days/1M pop
6. Deaths in the last 7 days
7. Deaths in the preceding 7 days
8. Weekly Death % Change
9. Deaths in the last 7 days/1M pop
10. Population

Source

Link : https://www.worldometers.info/coronavirus/weekly-trends/#weekly_table

Other Updated Covid Datasets

Link : https://www.kaggle.com/anandhuh/datasets

Please appreciate the effort with an upvote 👍

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

This map shows the incidence rate per 100,000 for all cancer types by county. Counties are shaded based on quartile distribution. The lighter shaded counties have lower cancer incidence rates. The darker shaded counties have higher cancer incidence rates. New York State Community Health Indicator Reports (CHIRS) were developed in 2012, and are updated annually to consolidate and improve data linkages for the health indicators included in the County Health Assessment Indicators (CHAI) for all communities in New York. The CHIRS present data for more than 300 health indicators that are organized by 15 different health topics. Data if provided for all 62 New York State counties, 11 regions (including New York City), the State excluding New York City, and New York State. For more information, check out: http://www.health.ny.gov/statistics/chac/indicators/. The "About" tab contains additional details concerning this dataset.

This map shows the percentage of high school drop outs by county. Counties are shaded based on quartile distribution. The lighter shaded counties have lower percentages of high school drop outs. The darker shaded counties have higher percentages of high school drop outs. New York State Community Health Indicator Reports (CHIRS) were developed in 2012, and are updated annually to consolidate and improve data linkages for the health indicators included in the County Health Assessment Indicators (CHAI) for all communities in New York. The CHIRS present data for more than 300 health indicators that are organized by 15 different health topics. Data if provided for all 62 New York State counties, 11 regions (including New York City), the State excluding New York City, and New York State. For more information, check out: http://www.health.ny.gov/statistics/chac/indicators/. The "About" tab contains additional details concerning this dataset.

U.S. consumers were asked how much money they spent on average on groceries per week. The findings present that U.S. households' weekly grocery expenditure amounted to about 165 U.S. dollars in 2024. Between 2019 and 2024, the average weekly expenditure grew exponentially, favored by the pandemic first and inflation after. Food affordability Since the pandemic, food affordability has been a challenge for consumers around the world, leading to changes around their food consumption. In the United States, meats, specialty foods and snacks are among the less purchased products, other changes include the purchase of generic products to save money on groceries. Generational differences Due to the rise of online grocery shopping, the difference in generational consumer behavior is significant. Millennials are most likely to shop online for their groceries, followed by Gen Z, while older generations prefer in-store shopping. When it comes to shopping frequency, those aged between 25 and 34 tended to shop more often compared to the youngest and oldest generations.

This map shows the percentage of premature deaths of individuals less than 75 years old by county. Counties are shaded based on quartile distribution. The lighter shaded counties have a lower percentage of premature deaths. The darker shaded counties have a higher percentage of premature deaths. New York State Community Health Indicator Reports (CHIRS) were developed in 2012, and are updated annually to consolidate and improve data linkages for the health indicators included in the County Health Assessment Indicators (CHAI) for all communities in New York. The CHIRS present data for more than 300 health indicators that are organized by 15 different health topics. Data if provided for all 62 New York State counties, 11 regions (including New York City), the State excluding New York City, and New York State. For more information, check out: http://www.health.ny.gov/statistics/chac/indicators/. The "About" tab contains additional details concerning this dataset.

This dataset contains the latest Community Health Indicator Report (CHIRS) data. New York State Community Health Indicator Reports (CHIRS) were developed in 2012, and are updated annually to consolidate and improve data linkages for the health indicators included in the County Health Assessment Indicators (CHAI) for all communities in New York. The CHIRS present data for more than 300 health indicators that are organized by 15 different health topics. Data if provided for all 62 New York State counties, 8 regions (including New York City), the State excluding New York City, and New York State. For more information, check out: http://www.health.ny.gov/statistics/chac/indicators/ or go to the “About” tab.

This map shows the Lyme Disease incidence rate per 100,000 by county. Counties are shaded based on quartile distribution. The lighter shaded counties have lower incidence rates of Lyme Disease. The darker shaded counties have higher incidence rates of Lyme Disease. New York State Community Health Indicator Reports (CHIRS) were developed in 2012, and are updated annually to consolidate and improve data linkages for the health indicators included in the County Health Assessment Indicators (CHAI) for all communities in New York. The CHIRS present data for more than 300 health indicators that are organized by 15 different health topics. Data if provided for all 62 New York State counties, 11 regions (including New York City), the State excluding New York City, and New York State. For more information, check out: http://www.health.ny.gov/statistics/chac/indicators/. The "About" tab contains additional details concerning this dataset.

The column chart illustrates the statewide rates of cardiac catheterization utilization by gender and payer for the measurement year. The chart uses statewide average rates of all insurance plans. Removing the statewide average filter is not recommended. For more information please visit http://www.health.ny.gov/health_care/managed_care/reports/quality_performance_improvement.htm#link5. The "About" tab contains additional details concerning this dataset.

This line chart compares the median costs vs. median charges for renal failure with a major severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.

This dataset tracks the updates made on the dataset "Community Health Indicator Reports (CHIRS): Latest Data" as a repository for previous versions of the data and metadata.

Analysis of ‘Covid19 in World Countries-Latest Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/anandhuh/covid19-in-world-countrieslatest-data on 12 November 2021.

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

Content

This dataset contains Covid-19 data of world countries as on November 10, 2021

Attribute Information

• Country - Name of world countries
• Total Cases - Total number of Covid-19 cases
• Total Deaths - Total number of Deaths
• Total Recovered - Total number of recovered cases
• Active Cases - Total number of Active cases
• Total Cases/1 mil population- Total Cases per 1 million of the population
• Death/1 mil population - Total Deaths per 1 million of the population
• Total Tests - Total number of Covid tests done
• Tests/1 mil population - Covid tests done per 1 million of the population
• Population - Population of the country

Source

Link : https://www.worldometers.info/coronavirus/#countries

Other Updated Covid 19 Datasets

Link : https://www.kaggle.com/anandhuh/datasets

Upvote if you find it useful 🙏

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

According to data. in 2022, the segment of discounts in Italy reported an increase of 14.2 percent in the organic food consumption in the country compared to the previous year. On the other hand, traditional stores reported a decrease of 6.2 percent compared to 2021.

This line chart compares the median cost vs. median charge for chest pain with a minor severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.

The latest data on flood depth sensing equipment collected by IoW (Internet of Things for Water Resources)

This line chart compares the median cost vs. median charge for vaginal deliveries with a minor severity of illness by hospital. The dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided.For more information, check out: http://www.health.ny.gov/statistics/sparcs/. The "About" tab contains additional details concerning this dataset.

The latest numerical data of scour depth sensing equipment collected by IoW (Internet of Things for Water Resources)

The number of private households living in a dwelling with piped water, divided by the total number of private households. Access to piped water is determined using the IPUMS WATSUP variable (WATSUP greater or equal 10 & WATSUP less or equal 18): https://international.ipums.org/international-action/variables/WATSUP#codes_section. There are inconsistencies in the treatment of piped water that is accessed only by going outside of the dwelling in WATSUP. In some censuses this would be reported as lack of piped water, but in others this information is included as subcategories of "piped water". Similary, in some censuses, piped water implicitly means water from a public network. Water from other sources, such as a well, could have been piped into the dwelling but not register as piped water in WATSUP. For this indicator, households accessing water inside or outside the building or lot are considered to have access to piped water. For more information, see https://international.ipums.org/international-action/variables/WATSUP#description_section. This indicator is calculated for private households only. Water supply information is not reported for group quarters such as institutions and other collective dwellings for most censuses. For this reason, group quarters are excluded from both numerator and denominator of this indicator. Group quarters are identified using the IPUMS GQ variable: https://international.ipums.org/international-action/variables/GQ#codes_section.This dataset contains all existing disagregations and, and the latest vintage data for the indicator.Each disaggregation is in a separate column. There is a single row per geography.Data download: CSV File Shape File File GeodatabaseDomain: POPULATIONSubdomain: Household characteristicsGeography Level: Geolev1Measure: PercentageUniverse: Private householdsAge Universe: AllSex Universe: BothMarital Status Universe: AllNotes:Individuals are not organized into households in the following samples: Canada 1971, Chile 1960, Costa Rica 1963, Ecuador 1962, Honduras 1961. These samples are included for this indicator, but because these are samples of individuals rather than households, the indicator values may not be fully comparable to those from household samples.