Every two seconds, sensors measuring the United States' electrical grid collect 3 petabytes of data – the equivalent of 3 million gigabytes. Data analysis on that scale is a challenge when crucial information is stored in an inaccessible database. But researchers at Purdue University are working on a solution, combining quantum algorithms with classical computing on small-scale quantum computers to speed up database accessibility. They are using data from the U.S. Department of Energy National Labs' sensors, called phasor measurement units, that collect information on the electrical power grid about voltages, currents and power generation. Because these values can vary, keeping the power grid stable involves continuously monitoring the sensors. Sabre Kais, a professor of chemical physics and principal investigator, will lead the effort to develop new quantum algorithms for computing the extensive data generated by the electrical grid. "Non-quantum algorithms that … [Read more...] about Quantum Computers Tackle Big Data With Machine Learning
Qpcr data analysis excel
For decades, Microsoft has been a leader in advanced data tools. From Excel spreadsheets to Visual Basic for Applications (VBA), to Microsoft Access database management system, businesses have been relying on these tools to help solve problems, automate complicated processes, and deliver data in a digestible manner. If your company or business uses one or more of these services but you're not as well-versed as you'd like, Android Central Digital Offers has a great deal for you. You can get Lifetime Access to the Microsoft Data Analysis Bundle for just $29. Valued at over $1100, that's a savings of 97%! This bundle includes more than 30 hours of content split across four courses on the following Microsoft Advanced Data Tools: Microsoft Power BI Advanced Excel Advanced VBA Advanced Microsoft Access Training yourself on these services is a great example of professional development, and shows potential employers that you're serious about learning new tools and skills. Don't miss out on … [Read more...] about Save 97% on the Microsoft Data Analysis Bundle!
You can turn a stacked bar chart into a project-savvy Gannt chart. Make a four-column table with "Start," "Stage," "Date" and "On Task" across the top row. In Cells B2 through B7, enter project stages like Plan, Build, Approve, etc. In Cell A2, under Start, enter the start date for the first stage item, then in Cells D2 through D7 (under On Task), enter the number of days for each stage to complete. In Cell C2 enter "=A2" and format the cell as General. You'll see a number like 43205, which is Excel's time/date code needed for the chart layout. Finally, in C3 enter "=C2+D2", then copy and paste this formula into cells C4 through C7. Select the cells you’ve entered from Column B through D and click Insert. Click the column chart icon and then the stacked bar chart. Now let’s bring the chart into focus. Right-click the X-axis labels and click Format Axis. In the Axis Options pane, click the Number item and, in Category, select Date from the drop-down. In Type, select a … [Read more...] about 10 spiffy new ways to show data with Excel
One of the great things about R is the thousands of packages users have written to solve specific problems in various disciplines -- analyzing everything from weather or financial data to the human genome -- not to mention analyzing computer security-breach data.Some tasks are common to almost all users, though, regardless of subject area: data import, data wrangling and data visualization. The table below show my favorite go-to packages for one of these three tasks (plus a few miscellaneous ones tossed in). The package names in the table are clickable if you want more information. To find out more about a package once you've installed it, type help(package = "packagename") in your R console (of course substituting the actual package name ).My favorite R packages for data visualization and munging Package Category Description Sample Use Author dplyr data wrangling, data analysis The essential data-munging R package when working with data frames. Especially useful for operating … [Read more...] about Best R packages for data import, data wrangling & data visualization
So you've read your data into an R object. Now what?Examine your data objectBefore you start analyzing, you might want to take a look at your data object's structure and a few row entries. If it's a 2-dimensional table of data stored in an R data frame object with rows and columns -- one of the more common structures you're likely to encounter -- here are some ideas. Many of these also work on 1-dimensional vectors as well.Many of the commands below assume that your data are stored in a variable called mydata (and not that mydata is somehow part of these functions' names).[This story is part of Computerworld's "Beginner's guide to R." To read from the beginning, check out the introduction; there are links on that page to the other pieces in the series.]If you type:head(mydata)R will display mydata's column headers and first 6 rows by default. Want to see, oh, the first 10 rows instead of 6? That's:head(mydata, n=10)Or just:head(mydata, 10)Note: If your object is just a 1-dimensional … [Read more...] about Beginner’s guide to R: Easy ways to do basic data analysis