I converted a .csv file into a GAUSS data file (.dat) using ATOG. I was careful enough to remove missing observations and rows/columns with string values and there were no conversion errors.
Now I'm trying to read data from the ".dat" file into GAUSS and it just seems incredibly convoluted.
Here is what I have so far:
dataset_filename = "my_data.dat"; dataset_handle = dataopen(dataset_filename,"read"); nobs = rowsf(dataset_handle); dataset = readr(dataset_handle,nobs);
This works, but is this the easiest way to store all of the rows and columns saved in the ".dat" file into a variable called "dataset"? Or am I just not seeing an obvious answer?
You can load all of the rows and columns of a GAUSS dataset by just passing your dataset name to the
loadd function like this:
// Load all rows and columns from 'my_data.dat' dataset = loadd("my_data.dat");
You might also like to know that you can also read tabular CSV files with the
loadd function. For example, let's say you have a file named
players.csv which looks like this:
"height","weight" 68,221 79,268 74,195
then you could load all the data with
loadd like this:
p = loadd("players.csv");
p would contain:
68,221 79,268 74,195
Alternatively, you could use the
csvReadM command to load the CSV data into a GAUSS matrix like this:
// Load all data starting at row 2 // from 'players.csv' p2 = csvReadM("players.csv", 2);