Data Types - Arrays and Records

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Data Type - Arrays: 1D/Lists
Arrays - a data structure that can store a group of data values, of the same type, under the same name  They are the most useful when you have lots of related data that you want to store and it doesn't make sense to use separate variables - eg. names of people in a class  Element - each piece of data in an array - each element can be accessed using its position (or index) in the array Creating arrays:  Python - people = {"Mark", "Adam", "Shelly"} Pseudocode - people <- {"Mark", "Adam", "Shelly"}     2.. Retrieving elements:  Remember in pseudocode, positions are numbered starting at 0 and in python, positions are numbered starting at 1  Python - print people[1]  Pseudocode - OUTPUT people[0]
   3. Changing elements: Python - people[1] = "Tami" Pseudocode - people[0] <- "Tami"     4. Number of elements: Python - len(people) Pseudocode - LEN(people) Combining these array functions with FOR loops, will give you a systematic way of accessing and changing all of the elements in an array

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Data Type: Arrays - 2 Dimensional Arrays
Creating arrays:  trees <- [['oak', 'ash'], ['beech', 'cedar'], ['pine', 'elm']] Positions of elements:  The position of an element is usually written [a][b] or [a,b], where a represents the separate list and b represents the position inside the individual lists.  trees[0][0] - oak  trees[0][1] - ash trees[2][0] - pine  Length of an array or a list in the array: Length of an array says how many individual lists there are in the array = LEN(trees) - 3  Length of a list in an array says how many elements there are in the list = LEN(trees[1]) - 2  
Rowsandcolumns (binary/octet-stream)
Pie de foto: : You can think of a 2D array as a grid or table

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