endsWith¶

Purpose¶

Returns a 1 if a string ends with a specified pattern.

Format¶

mask = endsWith(str, pat)¶

Parameters:	str (Nx1 string array or dataframe of type category or string) – The data to be searched. pat (String or dataframe of type category or string) – The pattern to search for at the end of str.
Returns:	mask (Nx1 vector) – A matrix of the same size as str with a 1 in any element that ends with the value of pat, otherwise 0.

Examples¶

Example 1¶

The following example searches for all observations of the variable make in the auto2.dta dataset that end with "bird" .

// Load 3 variables from the dataset
fname = getGAUSSHome("examples/auto2.dta");
auto = loadd(fname, "make + price + mpg");

// Specify pattern to search for
pat = "bird";

// Find all makes that end with 'bird'
mask = endsWith(auto[., "make"], pat);

// Select observations if the corresponding
// row of mask equals 1.
auto_birds = selif(auto, mask);

print auto_birds;

This prints the following:

          make            price              mpg
Pont. Firebird        4934.0000        18.000000
 Pont. Sunbird        4172.0000        24.000000

Example 2: Select rows based on the ending text from 2 columns¶

In this example, we will select all rows where the first column ends with Apple and the second column ends with Cheese.

// Create 2, 4x1 string arrays
fruit = "Red Apple" $| "Grapefruit" $| "Green Apple" $| "Green Apple";
snack = "Cheddar Cheese" $| "Havarti Cheese" $| "Walnuts" $| "Swiss Cheese";

// Combine the string arrays into a dataframe
food = asdf(fruit $~ snack, "fruit", "snack");

print food;

      fruit            snack
  Red Apple   Cheddar Cheese
 Grapefruit   Havarti Cheese
Green Apple          Walnuts
Green Apple     Swiss Cheese

This time our pattern input needs to be a 1x2 string array with one search pattern for each column.

// Specify one string to search
// for in each column
pat = "Apple" $~ "Cheese";

// Find all fruits that end with 'Apple'
// and all snacks that end with 'Cheese'.
mask = endsWith(food, pat);

print mask;

0000000        1.0000000
0000000        1.0000000
0000000        0.0000000
0000000        1.0000000

As we can see above, our mask contains two columns that tell us which observations matched our search. Before we can use selif() to select the matching rows, we need to convert mask to a column vector with a 1 in the case where both columns matched. We will do that by summing across the rows and then using the dot equality operator to see which rows were summed to equal two.

mask2 = sumr(mask) .== 2;

// Select observations where the fruit ends with 'Apple'
// and the snack ends with 'Cheese'
apple_cheese = selif(food, mask2);

print apple_cheese;

      fruit            snack
  Red Apple   Cheddar Cheese
Green Apple     Swiss Cheese