A table is a data structure that stores information in a table format with rows and columns, each of which can be mnemonically labeled. For example, the following uses the table function to store some simple information for a doctor’s patients.
>>names= {'Harry', 'Sally', 'Jose'};
>>weights= [185; 133; 210]; % Note column vectors
>>heights= [74; 65.4; 72.2];
>>patients= table (weights, heights, 'RowNames', names)
patients=
weights heights
---- -----
Harry 185 74
Sally 133 65.4
Jose 210 72.2
This created a 3 x 2 table, with two variables named weights and heights.
There are many ways to index into tables, to either create a new table that is a subset of the original, or to extract information from the table into other types of data structures. Using parentheses to index, the result is another table; the indexing can be done using integers (as with arrays we have seen so far) or by using row or variable names.
>> patients(1:2, 1)
ans =
weights
_______
Harry 185
Sally 133
>> patients ( {'Harry' 'Jose'}, : )
ans =
weights heights
_______ _______
Harry 185 74
Jose 210 72.2
Using curly braces to index, the data can be extracted; in the following example, into a double matrix.
>> mat = patients{{'Harry' 'Jose'},:}
mat =
185.0000 74.0000
210.0000 72.2000
The summary function can be used for tables; it shows the variables and some statistical data for each.
>> summary (patients)
Variables:
weights: 3x1 double
Values:
min 133
median 185
max 210
heights: 3x1 double
Values:
min 65.4
median 72.2
max 74
