Specify the last names of patients as the row names of the tables. A table can have row names along its first dimension, labeling the rows, but is not required to have them. An inner join keeps only those table rows that match with respect to the key variables.Ĭreate two tables of patient data. When you join tables or timetable together using the join, innerjoin, and outerjoin functions, you can specify row labels as key variables.įor example, you can perform an inner join two tables together, using row names and a table variable together as key variables. When you group rows together using the rowfun, varfun, stack, and unstack functions, you can specify row labels as grouping variables. To rename a variable, you can access the VariableNames property of the table and change its name there.Use Row Labels as Grouping or Key Variables You can perform arithmetic with datetime variables, just as you can with numeric variables. Note that OutageTime and RestorationTime are datetime variables.

meanByRegion = varfun(omean,T, 'GroupingVariables', 'Region'. I'm going to use the same omean function I specified above. Specify Loss and Customers as the input variables, and calculate the mean values by region for these two variables. It's a categorical variable, making it especially convenient to use as a grouping variable. Specify Region as the grouping variable in this table. You can use grouping variables with the varfun function I described above. For more on grouping variables, see Grouping Variables to Split Data. Then you can apply a function to each group within each table variable and the results. The grouping variables define groups into which you split the other table variables. To answer this question, you can start by specifying one or more table variables as grouping variables.

For example, what is the difference in the mean power loss between the Northeast and Southwest regions? Perform Calculation on Groups in Numeric VariablesĪ more interesting view of the table is to group the data, and start looking for differences between the groups. And since the variables have some NaN values, I'm going to wrap mean in an anonymous function so I can use the 'omitnan' flag. Here I'm going to subscript into T for the numeric variables and calculate the mean of each one. You can specify the type of variable with the vartype function. However, you might want to apply a function only to variables of a particular type. varfun is particularly useful for applying a function and returning the results in another table. You also can apply a function to every table variable, using the varfun function. totalCustomers = sum(T.Customers, 'omitnan') For example, calculate the total number of customers affected by power outages using the sum function, omitting any NaN values that might be in T.Customers. One way is to use dot notation to refer to table variables by name and perform calculations. Once data is in a table, you can perform calculations on different table variables. Perform Calculation on Each Numeric Variable T has two categorical variables (specified with %C), two datetime variables ( %D) and two numeric variables ( %f). Since I want to specify the data types of the table variables, I use the Format name-value pair argument. If T is a timetable, then A does not include the row times. If T is a table with row names, then A does not include the row names. SouthWest 12:18 458.98 1.8202e+06 16:50 winter storm Syntax A table2array (T) Description example ) A The output A does not include the table properties in. Region OutageTime Loss Customers RestorationTime Cause To display the first five rows, use table indexing. The file outages.csv contains simulated data for electric power outages over a period of 12 years in the United States. I'm going to use readtable to read data from a sample file that ships with MATLAB. You can create a table using the table function, the Import Tool, or the readtable function. Today I will show several different ways to apply functions to groups in tables.įirst, let's create a table. And you can specify groups within table variables, to perform calculations on those groups. You can access table data by row, by variable, or by variable name. The variables in a table can have different data types, but must have the same number of rows. Tables are convenient containers for column-oriented data. Use Groups in Multiple Calculations and Tabulate Results.Multiple Variables as Input Arguments to Function.Perform Calculation on Groups in Numeric Variables.Perform Calculation on Each Numeric Variable.

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