A list comprehension expression is a powerful way to process structures like our matrix.
To extract the second column of our sample matrix, grab rows by simple indexing because the matrix is stored by rows comprehension:
M = [[1, 2, 3], # A 3 ? 3 matrix, as nested lists [4, 5, 6], # Code can span lines if bracketed [7, 8, 9]] # www . ja v a2s.com col2 = [row[1] for row in M] # Collect the items in column 2 print( col2 ) print( M ) # The matrix is unchanged
List comprehensions derive from set notation.
They build a new list by running an expression on each item in a sequence, one at a time, from left to right.
List comprehensions are coded in square brackets and are composed of an expression and a looping construct that share a variable name (row, here).
The preceding list comprehension means: "Give me row[1] for each row in matrix M, in a new list."
The result is a new list containing column 2 of the matrix.
M = [[1, 2, 3], # A 3 ? 3 matrix, as nested lists [4, 5, 6], # Code can span lines if bracketed [7, 8, 9]] # w w w.ja v a 2 s .c o m print( [row[1] + 1 for row in M] ) # Add 1 to each item in column 2 print( [row[1] for row in M if row[1] % 2 == 0] ) # Filter out odd items
The first operation here adds 1 to each item as it is collected.
The second uses an if clause to filter odd numbers out of the result using the % modulus expression (remainder of division).
List comprehensions make new lists of results, but they can iterate over any iterable object.
Here, for instance, we use list comprehensions to step over a hardcoded list of coordinates and a string:
M = [[1, 2, 3], # A 3 ? 3 matrix, as nested lists [4, 5, 6], # Code can span lines if bracketed [7, 8, 9]] # w w w . j av a2s. c om diag = [M[i][i] for i in [0, 1, 2]] # Collect a diagonal from matrix print( diag ) doubles = [c * 2 for c in 'test'] # Repeat characters in a string print( doubles )
These expressions can collect multiple values, as long as we wrap those values in a nested collection.