30 Data Sets to Uplift your Skills in Data Science

Data Science Dojo has added 30 data sets to its repository which is freely available for data science and AI enthusiasts. The repository carries a diverse range of themes, difficulty levels, sizes and attributes. The data sets are categorized according to varying difficulty levels to be suitable for everyone. They offer the ability to challenge one's knowledge and get hands-on practice to boost their skills in areas, including but not limited to, exploratory data analysis, data visualization, data wrangling and machine learning.

The data sets below have been sorted with increasing level of difficulty for convenience (Beginner, Intermediate, Advanced) . We recommend to test yourself with all the distinct data sets we’ve provided. We’ve presented a challenging question with each one, however, feel free to use them in any way you wish.

1) Find out the age of Abalone from physical measurements

Level: Beginner Recommended Use: Regression Models Domain: Automobiles

This beginner level data set has 4,177 rows, 9 columns, physical measurements of abalones, and the number of rings (representing age). The age of an abalone is usually determined by a boring and time-consuming task. Therefore, physical measurements, which are easier to obtain, can be used to predict the age.

2) Predict student's knowledge level

Level: Beginner Recommended Use: Classification/Clustering Domain: Education/Web

This data set has 403 rows and 6 columns. It is a real data set about the students' knowledge status about the subject of Electrical DC Machines.

3) Can you predict the price of a house?

Level: Beginner Recommended Use: Regression Models Domain: Real Estate

With 414 rows and 7 columns related to various attributes of a house, this data set provides the market historical data of real estate valuations which are collected from Sindian Dist., New Taipei City, Taiwan.

4) Can you estimate location from WiFi Signal Strength?

Level: Beginner Recommended Use: Classification Models Domain: Mobile/Location

This beginner level data set has 2,000 rows and 8 columns. The data contains wifi signal strength observed from 7 wifi devices on a smartphone collected in indoor space which could be used to estimate the location in one of the four rooms.

5) Predict acceptability of a car

Level: Beginner Recommended Use: Classification Models Domain: Automobile

The data set has 1,728 rows and 7 columns in which car attributes, such as price and technology, are described across 6 variables such as "Buying Price", "Maintenance", and "Safety" etc. There are multiple alternatives under each of the 6 variables. Car's acceptability, the seventh attribute, is the outcome variable.

6) Predict seminal quality of an individual

Level: Beginner Recommended Use: Regression/Classification Models Domain: Healthcare/Life

This data set has 10 attributes. It includes semen samples of 100 volunteers, analyzed according to the WHO 2010 criteria. It can be used to determine if it's possible to reach a diagnosis without a laboratory approach, which includes expensive tests that are sometimes uncomfortable for the patients. Attributes presented in this data set can be taken easily using a questionnaire to estimate sperm concentration.

7) Estimate chance of Bankruptcy from Qualitative parameters by experts

Level: Beginner Recommended Use: Classification Models Domain: Finance/Banking

This data set has 250 rows and 7 columns. It contains 6 qualitative parameters from experts which can be used to predict bankruptcy.

8) Can you predict the fuel-efficiency of a car?

Level: Intermediate Recommended Use: Regression Models Domain: Automobiles

This data set has 398 rows, 9 columns, and provides mileage, horsepower, model year, and other technical specifications for cars.

9) Was that chest pain an indicator of a heart disease?

Level: Intermediate Recommended Use: Classification Models Domain: Health Sciences

This data set provides health examination data among 303 patients who were presented with chest pain and might have been suffering from heart disease. The data set has 14 attributes to find whether the diagnosed patient were found to have a heart disease or not.

10) Predict total number of demand of orders

Level: Intermediate Recommended Use: Regression Models Domain: Business

This intermediate level data set has 60 rows and 13 columns. The data was collected during 60 days, and is from a real database in a Brazilian logistics company. It has twelve predictive attributes and a target that is the total orders for daily treatment.

11) Find out if a donor will give blood in March 2007

Level: Intermediate Recommended Use: Classification Models Domain: Business

This data set has 748 instances and 5 attributes. The data is from a donor database, Blood Transfusion Service Center in Hsin-Chu City, in Taiwan. The center drives their blood transfusion service bus to a university in Hsin-Chu City to gather blood donated about every three months.

12) Forecast Pollution Level of a City

Level: Intermediate Recommended Use: Regression Models Domain: Environment

This data set has 43,824 rows and 13 columns. It contains the PM2.5 data from the US Embassy in Beijing. Meteorological data from Beijing Capital International Airport is also included. The data set can be used for pollution level forecasting using the Air Quality attributes provided. It will also offer experience in Multivariate Time Series Forecasting.

13) Will the patient survive for at least one year after a heart attack?

Level: Intermediate Recommended Use: Classification Models Domain: Automobiles

This data set has 132 rows and 12 columns. It provides data that can be used for classifying if patients will survive for at least one year after a heart attack. All patients listed in the data set suffered heart attacks at some point in the past. Some are still alive and some are not.

14) Estimate compressive strength of concrete

Level: Intermediate Recommended Use: Regression Models Domain: Civil Engineering/Construction

This set has 1,030 rows and 9 columns. Concrete is the most important material in civil engineering. The concrete compressive strength is a highly nonlinear function of age and ingredients. The actual concrete compressive strength (MPa) for a given mixture under a specific age (days) was determined from a laboratory.

15) Discover patterns relating liver disorder and alcohol consumption

Level: Intermediate Recommended Use: Classification/Regression/Clustering Models Domain: Healthcare

This data set has 345 rows and 7 columns. The data set does not contain any variable representing presence or absence of a liver disorder. The first five columns represent the result of various blood tests which may be of use in diagnosing alcohol-related liver disorders. The sixth represents the number of alcoholic drinks consumed per day by the subject (self-reported).

Level: Intermediate Recommended Use: Clustering/Regression/Classification Models Domain: Business/Finance

This data set has 750 rows and 16 columns. It contains weekly data for the Dow Jones Industrial Index, used in computational investing research. Each record is data for a week and has the percentage of return that stock has in the following week. Ideally, this could be used to determine which stock will produce the greatest rate of return in the following week.

17) Assess heating and cooling load requirements of building

Level: Intermediate Recommended Use: Regression/Classification Models Domain: Energy

This data set has 768 rows and 10 columns. It can be used for assessing the heating load and cooling load requirements of buildings (that is, energy efficiency) as a function of building parameters. The buildings differ with respect to the glazing area, the glazing area distribution, and the orientation, amongst other parameters.

18) Determine the type of glass using oxide content

Level: Intermediate Recommended Use: Classification Models Domain: Physical

This data set has 214 rows and 10 columns. It provides details about 6 types of glass, defined in terms of their oxide content (i.e. Na, Fe, K, etc).

19) Predict chance of survival

Level: Intermediate Recommended Use: Classification Models Domain: Healthcare

This data set has 155 rows, 20 columns, and provides various attributes of a patient suffering from hepatitis. This can be used to predict the patient’s chance of survival or for other purposes.

20) Find patterns from spending data at wholesale

Level: Intermediate Recommended Use: Classification/Clustering Domain: Business/Retail

This data set has 440 rows and 8 columns. The data refers to clients of a wholesale distributor. It includes the annual spending in monetary units (m.u.) on diverse product categories.

21) Group similar travel reviews

Level: Intermediate Recommended Use: Clustering/Classification Models Domain: Web

This data set, populated by crawling TripAdvisor.com, has 980 rows and 11 columns. It includes reviews on destinations in 10 categories mentioned across East Asia. Each traveler rating is mapped as Excellent(4), Very Good(3), Average(2), Poor(1), and Terrible(0); and average rating is used against each category per user.

22) Relate returns of Istanbul Stock Exchange with other international indices

Level: Intermediate Recommended Use: Regression/Classification Models Domain: Business/Finance

This data set has 536 rows and 9 columns. It includes returns of Istanbul Stock Exchange (ISE) with seven other international indices; SP, DAX, FTSE, NIKKEI, BOVESPA, MSCE_EU, MSCI_EM. It can be used to find a predictive relationship between the ISE100 and other international stock market indices.

23) Predict bike rental count (hourly/daily) based on the environmental & seasonal settings

Level: Intermediate Recommended Use: Regression Models Domain: Social

This data set, consisting of 17,379 rows and 17 columns, contains the hourly and daily count of rental bikes between years 2011 and 2012 in Capital bike-share system with the corresponding weather and seasonal information. Bike-sharing rental process is highly correlated to the environmental and seasonal settings.

24) Detect Room Occupancy through Light, Temperature, Humidity and CO2 sensors

Level: Intermediate Recommended Use: Classification Models Domain: Energy/Buildings

This data set has 20,560 rows and 7 attributes. It provides experimental data used for binary classification (room occupancy of an office room) from Temperature, Humidity, Light, and CO2. Ground-truth occupancy was obtained from time stamped pictures that were taken every minute.

25) Estimate whether a person’s income exceeds \$50K/year:

Level: Intermediate Recommended Use: Classification Models Domain: Social/Government

This data set was extracted from the census bureau database. There are 48,842 instances of data set. It has 15 attribute which include age, sex, education level and other relevant details of a person.

26) Detect Autistic Spectrum Disorder (ASD) cases:

Level: Advanced Recommended Use: Classification Models Domain: Healthcare/Social Sciences

This advanced level data set has Autistic Spectrum Disorder (ASD) Screening Test Data for 704 adults and has 21 attributes including test takers' demographics. It also has 10 questions that test takers answered in screening tests. The status of a test taker on ASD is determined and recorded under Class/ASD variable.

27) Estimate the probability of Default

This data set has 30,000 rows and 24 columns. The data set could be used to estimate the probability of default payment by credit card client using the data provided.

28) Predict if a note is genuine

Level: Advanced Recommended Use: Classification Models Domain: Banking/Finance

This advanced level data set has 1,372 rows and 5 columns. Data was extracted from images of genuine and forged banknote-like specimens that were taken for the evaluation of an authentication procedure for banknotes, later digitized. Wavelet Transform tool was used to extract features from images.

29) Find a short term forecast on electricity consumption of a single home

Level: Advanced Recommended Use: Regression/Clustering Models Domain: Electricity

This data set has 2,075,259 rows and 9 columns. This data set provides measurements of electric power consumption in one household with a one-minute sampling rate over a period of almost 4 years. Different electrical quantities and some sub-metering values are available.

30) Predict the number of shares on social networks

``````            </div></div>