Then use either read.table, read.csv or the Import dataset button in RStudio to read your table, and in case of doubt, begin with the default settings, which are often sensible.
Open your favourite spreadsheet software, remove all the colours and formatting, make sure to have only one header row with short and simple column names (avoid any special characters R will turn them to full stops), remove empty columns above and to the left of the table and export the sheet in to plain text, tab separated or comma separated. General tip: keep it as simple as possible. Therefore, let me share a few things that I’ve picked up while trying to read data into R. What is the most important thing about using any statistics software? To get your data into it in the first place! Unfortunately, no two datasets are the same and many frustrations await the beginner. This is because I believe (firmly) that importing data is the major challenge for beginners who want to analyse their data in R. These can then be read back in any format.I’ve written before about importing tabular text files into R, and here comes some more. Extra string variables can be created from value labels when writing to delimited ASCII, described by a schema.An extra variables can be created from the sheet name when combining worksheets.Directory recursion is now available in the wildcard copy command.
What is your time worth?įast transfers aren fast if you have to spend time puzzling over how to set them up. Of course you could use other tools to do what Stat/Transfer does, but it would take you hours, days and even weeks of effort to duplicate what Stat/Transfer does in a few seconds. Most transfer operations take just a few seconds and few clicks of the mouse. A variety of options (all with sensible defaults) allow you to tailor your transfer so that it meets the needs that you have today and in the future. It is easy to select variables, cases and data types.
With Stat/Transfer you can produce just the output you need. Because this program reflects the entire state of your options settings as well as all of the other information entered in the user interface, it allows you to thoroughly document your data transfer. It can also produce a Stat/Transfer command processor file that will enable you to re-run the transfer with just a few clicks. Stat/Transfer can automatically produce a log documenting your transfer operations. All of your metadata – value labels, variable labels and missing values - are accurately and effortlessly transformed. Stat/Transfer moves your data from one program to another with no loss of precision, while producing the smallest datasets possible. This makes it straightforward to set up fully automatic batch procedures for repetitive tasks. In addition to the standard graphical user interface, a command processor allows you to run a transfer in batch mode. Furthermore, you gain this speed and accuracy without losing flexibility, since Stat/Transfer allows you to select just the variables and cases you want to transfer.
Stat/Transfer can save hours and even days of manual labour, while at the same time eliminating error. In addition to converting the formats of variables, Stat/Transfer also processes variable names, missing values, and value and variable labels automatically. Stat/Transfer also allows control over the storage format of your output variables. Stat/Transfer preserves all of the precision in your data, while automatically minimizing the size of your output data set. Stat/Transfer will automatically read statistical data in the internal format of one of the supported programs and will then transfer as much of the information as is present and appropriate to the internal format of another. Stat/Transfer removes this barrier by providing an extremely fast, reliable and automatic way to move data.
For those in possession of data sets with many variables, it represents a serious impediment to the use of more than one program. Manual transfer is not only time-consuming, it is error-prone. Stat/Transfer is designed to simplify the transfer of statistical data between different programs.