How did the COVID-19 pandemic change how people at different income levels spent? What impact did economic stimulus measures have on purchases? Consumer Expenditure Surveys (CE) could help you answer these questions and more.Continue reading
Have you tried working with what look like text data in R only to get back a number or an error about comparing or replacing elements? If this sounds familiar, you may have been working with factor data. Read on for more about how to create and handle factor data in R.Continue reading
Did you (or your company, or your government…) try something new? You’ll want to know whether that change made a difference. Fortunately, the R statistical programming language offers easy-to-run tests that can help you compare performance before and after the policy went into effect.Continue reading
Think about your last friendly debate, mind-blowing lecture, or presidential tweet. Did someone make a quantitative claim that seemed hard to believe? If you can gather the data, you have the power to check the facts and come to your own evidence-based conclusion.
Let’s take an example: In the 2019 State of the Union Address, President Donald Trump stated, “the United States is now the number one producer of oil and natural gas in the world.”Continue reading
Need macroeconomic data for more than 128 countries? CEIC offers metrics including GDP, CPI, Forex rates, imports, exports, retail sales, and investment as well as premium data for Brazil, Russia, India, and China, letting you match up and download data from multiple sources for further research.
Let’s say you need to compare India’s and Russia’s gross domestic product (GDP) and quarterly imports from China from 1990 through 2015.Continue reading
Lippincott Library has a new resource for your data needs: Data-Planet. Data-Planet offers a wide array of statistical and economic data – you can find everything from historical prices of oil and natural gas, to annual lobbying expenditures by US lobbyists, to the number of houses built in a given year, to the average travel time to work in a particular state. You can even combine multiple data sets to look at them side-by-side.
But how do you find data? You can start broad with a keyword search to find any data sets with those keywords in the title or description or you can browse through the available data by topic or by source. For example, click Browse by Subject to browse through Data-Planet‘s Banking, Finance, and Insurance or Housing and Construction data. Click Browse by Source to look at their data from the World Bank, the IMF, Dow Jones, and many other sources.
You can click the magnifying glass to the right of the search bar to find US State Statistical Overviews and International Statistical Overviews. From there, click a state or country to generate a list of all available data sets about that state or country. If you get lost, just click Help in the upper-right corner to find a map – you can check Data-Planet‘s general Help Guide or look through their subject-specific guides.
So now that you know how to find data, let’s talk about what you can do with it. Once you choose a data set or two, you can visualize the data as a trend chart, pie chart, ranking bar graph, or a map. You can also look at the data in a table, add custom columns to the table, and export the data in a variety of formats.
Let’s say you want to compare the median listing price, median sale price, and median home value per square foot for all homes in Philadelphia County. Drill down through Browse by Subject – Housing and Construction – Zillow Real Estate Metrics – Other Metrics, then hold the Ctrl key and click each data set of interest to select multiple data sets. You can look at the whole data set, or use the filters at the top of the screen to limit your results to data from a specific state or county. Other data sets let you filter by industry, commodity, agency, bureau, and more.
Data-Planet‘s default visualization is a trend chart like the one above, but just click another visualization option to switch. The map visualization is particularly useful for granular data sets like real estate data, because much of the real estate data in Data-Planet goes to the county, zip code, or census-block level. You can even create a DOI (Digital Object Identifier) for any data visualizations you create in Data-Planet. The DOI records the date and time a particular visualization was created and acts as a permanent identifier anyone can use to cite your visualization. I created a DOI for the chart above, and you can check it out here: https://doi.org/10.6068/DP160527497B239.
These are just a few things you can do with Data-Planet. From looking at data across state lines or industries, to mapping demographic information, there’s a whole planet’s worth of data for you to explore. And if you get lost, you can always contact a Lippincott Librarian for help.