The Authorea server will work for all of the examples except the (aptly named) Python packages Pint and Uncertainties used for numerical calculations using units and/or uncertainties, as those packages are not currently installed on that server (but maybe someday?). That said, you will want to write, run, and store your own data and programs on your own system.  If you don't have access to a local Jupyter webserver with the packages you need, you will want to install and run Python and Jupyter on your own computer. The good news is that everything needed is available for free (except the computer)! See Section \ref{662059}Installing Python for instructions on how to do this. 

Importing and exporting data

There are many ways to import, export, and represent data in files. Here we provide just enough to get you started but it might very well be all you need. In these examples, we assume you have first entered the data into a spreadsheet program, then exported that data in 'CSV' (comma separated variable) file format. We use the CSV file format here because it is ubiquitous: all spreadsheets have the ability to export and import data in the CSV file format. Data in other common plain text file formats (such as tab delimited) can also be imported by making a few small modifications to the examples provided below. 

CSV spreadsheet file format

Let's look at a particular CSV data file titled Calibration_650nm.csv . The file consists of a single header row of text which we need to skip over when loading the numerical data, followed by three columns of data, one for each measured variable.
Here's what the data looks like in spreadsheet form (grid lines not shown):