If we have daily stock data, we could have them saved in different patterns. One way is to save them as stock ID, date, high, low, opening price, closing price, and trading volume. We could sort our stock ID and save them one after another. We have two ways to write a Python program to access IBM data: sequential access and random access. For sequential access, we read one line and check its stock ID to see if it matches our ticker. If not, we go to the next line, until we find our data. Such a sequential search is not efficient, especially when our dataset is huge, such as several gigabits. It is a good idea to generate an index file, such as IBM, 1,000, 2,000. Based on this information, we know that IBM's data is located from line 1,000 to line 2000. Thus, to retrieve IBM's data, we could jump to line 1,000 immediately without having to go through the first 999 lines. This is called random access.