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Interesting Data Sets

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Last Updated: 02 July 2021

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Data is ubiquitous but sometimes it can be hard to see forest for trees, as it were. Many companies of various sizes believe they have to collect their own data to see benefits from big data analytics, but it is simply not true. There are hundreds of free data sets available, ready to be used and analyzed by anyone willing to look for them. Below is a list of 35 of the most globally interesting things Ive come across, but there are many, many more in many different niches. Data. Gov http: / Data. Gov US Government pledged last year to make all Government Data available freely online. This site is first stage and acts as a portal to all sorts of amazing information on everything from climate to crime. US Census Bureau http: / www. Census. Gov / Data. Html wealth of information on the lives of US citizens covering population data, geographic data and education. Socrata is another interesting place to explore Government-relate data, with some visualisation tools build-in. European Union Open Data Portal http: / Open-Data. Europa. EU / en / Data / As above, but based on Data from European Union institutions. Data. Gov. UK http: / Data. Gov. UK / Data from the UK Government, including British National Bibliography-Metadata on all UK Books and publications since 1950. Canada Open Data is a pilot Project with many government and geospatial datasets. Datacatalogs. Org offers Open Government Data from the US, EU, Canada, CKAN, and more. CIA World Factbook https: / www. CIA. Gov / library / publications /-World-Factbook / Information on history, population, economy, government, infrastructure and military of 267 countries. Big Data Sources for 2016 healthdata. Gov https: / www. Healthdata. Gov / 125 years of US healthcare Data including claim-level Medicare Data, epidemiology and population Statistics. NHS Health and Social Care Information Centre http: / www. Hscic. Gov. UK / home Health Data sets from the UK National Health Service. UNICEF offers Statistics on the situation of women and children worldwide. The World Health Organization offers World hunger, health, and disease Statistics. Amazon Web Services Public datasets http: / aws. Amazon. Com / datasets huge resource of public data, including the 1000 Genome Project, attempt to build the most comprehensive database of human genetic information and NASA's database of satellite imagery of Earth. Facebook Graph https: / developers. Facebook. Com / docs / Graph-API Although much of the information on users ' Facebook profile is private, lot isnt-Facebook provides Graph API as a way of querying the huge amount of information that its users are happy to share with the world. Face. Com: fascinating tool for facial recognition data. UCLA made some of the data from its courses public. Data Market is a place to check out data relating to economics, healthcare, food and agriculture, and the automotive industry. Google Public Data explorer includes data from World development indicators, OECD, and human development indicators, mostly related to economic data and the world. Junar is a data scraping service that also includes data feeds. Buzzdata is a social data sharing service that allows you to upload your own data and connect with others who are uploading their data. Gapminder http: / www.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

120 Years of Olympic History

This content is about exploratory data analysis of 120 years of Olympic History. Datasets that are use are available publicly on Kaggle. All plots and visualizations are saved as HTML files that can be found on GitHub as well as in the kernel on my Kaggle profile. Links are provided at the end of this content. Plot 1: This plot is about visualiz i ng the top 5 sports in Olympic History based on the number of participants each year. Below method plots BarPolar chart in HTML file with mouseover, rotation, custom selection and zoom in / out functionality: plot 2: This plot describes the number of Gold, Silver and Bronze medals country-wise. Code for plotting the number of medals on the world map using plotly with HTML as output file is below: plot 3: This output shows a list of countries, in each sport, that have earned the maximum number of medals. Here, instead of country name, its code is show. Below is the code to filter and aggregate NOCs by grouping sport. Plot 4: Distribution of medals over different ages. Below code plots bar chart with HTML as output: plot 5: Number of male and female participants over years. Below is code plots graph: Link to GitHub project: Olympic History Link to Kaggle: Olympic History

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

1. Google Trends

In Google Trends, Google compiles and aggregates its search data, reflecting interest in certain keywords or concepts. While search data is not the same as poll or survey, these comparisons can provide insights, specifically for very recent developments. Surveys take time, often we get updated statistics only a few months or even a year later. So, core offering of Google Trends is that it enables you to look up keywords and compare their popularity, over time and per country. This brief tutorial shows you how to look up Google Trends, export data and create either a Datawrapper chart or map.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

2. National Climatic Data Center

1 . U.S. Local Climatological Data

Local Climatological Data (LCD)SamplePeriod of Record for Station Certification charges apply
Global-Hourly File AccessSamplePeriod of Record for Station
QCLCD ASCII FilesSampleQCLCD ASCII Files are no longer available. Please use the Global-Hourly File Access link above.
Edited Monthly (Online LCD)SampleCertification charges apply Available through 2017 ( No New LCD Publications after 2017 )
Edited Annual (Online LCD Annual)SampleCertification charges apply

Center for Operational Oceanographic Products and Services Operational Forecast System This Operational Forecast System models hydrodynamic data for select estuaries, lakes, and rivers in the United States to support navigation and coastal needs. It is produced by CO-OPS, which is part of the National Ocean Service. Hybrid Coordinate Ocean Model, Global Navy implementation of HYCOM is a successor to Global NCOM. This site hosts regions covering US Coastal waters as well as the Global Surface Model. Navy Coastal Ocean Model, Global Global NCOM was run by the Naval Oceanographic Office as Navys Operational Global Ocean-Prediction System prior to its replacement by Global HYCOM System in 2013. This site hosts regions covering US, European, West Pacific, and Australian Coastal waters as well as Global Surface Model. Navy Coastal Ocean Model, Regional Regional NCOM is a high-resolution Version of NCOM for specific areas. NCEI serves the Americas Seas, US East, and Alaska regions of NCOM. Naval Research Laboratory Adaptive Ecosystem Climatology Naval Research Laboratory AEC combine Ocean Model with Earth Observations to provide a synoptic view of the typical state of the Ocean for every day of year. This dataset covers the Gulf of Mexico and nearby areas. The National Centers for Environmental Prediction real Time Ocean Forecast System-Atlantic RTOFS-Atlantic is a Data-assimilating nowcast-Forecast System operated by NCEP. This dataset covers the Gulf of Mexico and most of the northern and central Atlantic.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

3. Global Health Observatory data

1 . U.S. Local Climatological Data

Local Climatological Data (LCD)SamplePeriod of Record for Station Certification charges apply
Global-Hourly File AccessSamplePeriod of Record for Station
QCLCD ASCII FilesSampleQCLCD ASCII Files are no longer available. Please use the Global-Hourly File Access link above.
Edited Monthly (Online LCD)SampleCertification charges apply Available through 2017 ( No New LCD Publications after 2017 )
Edited Annual (Online LCD Annual)SampleCertification charges apply

Curated by: World Health Organization example Data set: Universal access to reproductive Health As part of their core goal for better health information worldwide, World Health Organization make their Data on Global Health publicly available through Global Health Observatory. GHO acts as a portal with which to access and analyze health situations and important themes. Various data sets are organized according to themes, such as mortality, health systems, communicable and non-communicable diseases, medicines and vaccines, health risks, and so on. WHOs Health Statistics are the go-to source for Global Health information and is also used in the work of US Centers for Disease Control and Prevention.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

4. Data.gov.sg

Gov. Sg was first launched in 2011 as a government one-stop portal to its publicly available Datasets from 70 public agencies. To date, more than 100 apps have been created using government OPEN Data. New Data. Gov. Sg-launch in July 2015-go beyond being a data repository. It aims to make Government Data relevant and understandable to the public, through active use of Data visualisations and Data-driven articles. Key features of the portal are high quality data presented via dashboards for quick reference, shareable charts and tables of Datasets, and data blogs of social trends and Government policies explained using data analysis and visualisations. A new sub-site for developers was launched in April 2016. With a single application program interface key, developers and analysts can now access Government OPEN Data APIs from different agencies via portal instead of signing up with individual agencies. Currently, 14 high-frequency Datasets have been made available, including PSI readings from the National Environment Agency and available taxi locations from the Land Transport Authority. Create something interesting with government OPEN Data? Share it with the US! Drop US email at feedback Data. Gov. Sg, or Tweet to US datagovsg or message US on Facebook. We also welcome any requests for new Datasets or Data stories, and ideas on how we may further improve the site.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Next steps

The simplest way to describe any machine learning project is that its program that when given pieces of data it hasnt seen before, will process them based on previous experience and tell you something you do not already know. Data is at the core of nearly every business decision make. Human resources directors are gathering data from online resources to determine the best people to recruit and confirm details about them. Marketing departments are lasering in on market segmentation data to find consumers who are ready to buy, speeding up the sale-closing process whenever possible. Business executives must examine bigger trends in the market, such as changes in pricing of resources, shipping or manufacturing. Your project is only as powerful as the data you bring.


Step 1: Gathering the data

The choice of data entirely depends on the problem youre trying to solve. Picking the right data must be your goal, Luckily, almost every topic you can think of has several datasets which are public & free. 3 of my favorite free awesome websites for Dataset hunting are: kaggle which is so organize. Youll love how detailed their datasets are, They give you info on features, data types, number of records. You can use their kernel too and you wont have to download Dataset. Reddit is great for requesting datasets you want. Google Dataset Search which is still Beta, but it is amazing. UCI Machine Learning Repository, this one maintains 468 data sets as a service to the Machine Learning community. The good thing is that data is mean to end, in other words, quantity of data is important but not as important as the quality of it. So, if you like to be independent and create your own Dataset, begin with a couple of hundred lines and build up the rest as youre going. Thatll work too. Theres python library is called Beautiful Soup. It is a library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching and modifying parse tree. It commonly saves programmers hours or days of work.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Sources

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

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