Importing Data¶

File Formats¶

While being able to create functions, tables, and graphs is nice, in a laboratory setting, we really need to be able to work with data from lab equipment. Many software packages exist that interface with electronics (National Instruments’ LabVIEW is a prime example), and are able to provide text files with data. Sometimes this is in a “human-readable” format, but often it is in a computer-friendly format, such as TSV (tab-separated values), CSV (comma-separated values), or even XLS (Microsoft Excel format). Some may have headers in the data (a first row that names what each column represents), others may not. Here are some examples for reference:

**Table 1: Examples of Data Files with Same Data**
Format	Without Header	With Header
CSV	`without.csv`	`with.csv`
JSON	`without.json`	`with.json`
TSV	`without.tsv`	`with.tsv`
XLS	`without.xls`	`with.xls`
XLSX	`without.xlsx`	`with.xlsx`
XML	`without.xml`	`with.xml`

The CSV, TSV, XLS, and XLSX files should be easily opened in Excel or other spreadsheet software. The JSON and XML should be viewable in a web browser (these are less-likely to occur in a lab setting, but are fairly ubiquitous in some spheres).

From File to Usable¶

Once we have our data, we can easily import it to Mathematica with the Import command if it is one of the examples above or other well-defined type (as with exporting, in Mathematica‘s help, look at “guide/ListingOfAllFormats”). For example, for any of the above, we can write

table = Import["filename"]

and table will then have all the data in a 2-column list. If the data has a header, it can be accessed with table[[1]]. And the header can be removed with table = table[[2;;Length[table]]]. We can now do the usual things like plot the data with ListPlot, etc.

“Annoying” Formats¶

Sometimes we might have a format that isn’t built-in, and doesn’t have clean “delimeters” (that is, special symbols to mark the end of each entry in a list of entries). We might have a system that has entries that ar 4 space-separated values that are then separated by spaces. That would give a data file like this. Normal formats can’t tell the difference between entries because they aren’t based on having multiple lines, each with a single entry, or a similar construct. In this case, we can use ReadList. This function allows us to set a custom set of delimeters, and even the types of data for each entry.

ReadList["annoying.txt",
        {Number, Number, Number, Number},
        WordSeparators -> {" "},
        RecordSeparators -> {" "}]

Reads in {{0., 1., 12., 2.2}, {1.2, 4.2, 0.2, 2.4}, {2.4, 6.4, 1.2, 1.4}}.