Difference between revisions of "CSC111 Lab 8 2014"
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Revision as of 14:45, 24 March 2014
--D. Thiebaut (talk) 14:01, 24 March 2014 (EDT)
This lab deals with strings and list operations, and transforming strings into lists and lists into strings.
Contents
Splitting Strings
Work in the console, and try these different commands. Observe what the different operations do.
>>> line = "The quick, red fox jumped. It jumped over the lazy, sleepy, brown dog." >>> line >>> line.split() >>> words = line.split() >>> words >>> words[0] >>> words[1] >>> words[-1] >>> words[-2] >>> chunks = line.split( ',' ) # split on commas >>> chunks >>> chunks = line.split( '.' ) # split on periods >>> chunks >>> words >>> separator = "+" >>> newLine = separator.join( words ) # join the words into a new string and use separator as the glue >>> newLine >>> separator = "$$$" >>> newLine = separator.join( words ) # same but use $$$ as the glue >>> newLine >>> words # verify that you still have individual words in this list >>> newWords = [ words[0], words[3], words[4], words[7], words[8], words[12] ] # create a new list >>> newWords >>> " ".join( newWords ) # join strings in newWords list with a space
Mini Assignments
The solution program for the Exercises we saw in class on Monday and Wednesday contains good models of code that can be used to answer most of the challenges in this lab.
Challenge 1 |
- Use a judicious mix() of split() and join operations to convert the string
"1 China 1,339,190,000 9,596,960.00 139.54 3,705,405.45 361.42"
- into a new string:
"China 1339190000"
- Note 1: the lack of commas in the number! (Hints: string objects have replace methods that could prove useful here!)
- Note 2: that this line is taken from a table from this URL where the numbers after the country indicate a) the population, the area and population density expressed with square-kilometers, and the area and population density expressed with square-miles.
Challenge 2 |
- Given the following list, split it into individual lines, and apply your transformation to each line so that your program outputs only the country names and their populations.
China 1,339,190,000 9,596,960.00 139.54 3,705,405.45 361.42 India 1,184,639,000 3,287,590.00 360.34 1,269,345.07 933.27 United-States 309,975,000 9,629,091.00 32.19 3,717,811.29 83.38 Indonesia 234,181,400 1,919,440.00 122.01 741,099.62 315.99 Brazil 193,364,000 8,511,965.00 22.72 3,286,486.71 58.84 Pakistan 170,260,000 803,940.00 211.78 310,402.84 548.51 Nigeria 170,123,000 923,768.00 171.32 356,668.67 443.71 Bangladesh 164,425,000 144,000.00 1,141.84 55,598.69 2,957.35 Russia 141,927,297 17,075,200.00 8.31 6,592,768.87 21.53 Japan 127,380,000 377,835.00 337.13 145,882.85 873.17 Mexico 108,396,211 1,972,550.00 54.95 761,605.50 142.33 Phillipines 94,013,200 300,000.00 313.38 115,830.60 811.64 Vietnam 85,789,573 329,560.00 260.32 127,243.78 674.21 Germany 81,757,600 357,021.00 229.00 137,846.52 593.11 Ethiopia 79,221,000 1,127,127.00 70.29 435,185.99 182.04 Egypt 78,848,000 1,001,450.00 78.73 386,661.85 203.92 Iran 75,078,000 1,648,000.00 45.56 636,296.10 117.99
Challenge 3 |
- Take your solution for Challenge 2 and make it output
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- Figure out a way to take a string of the form "Pakistan 108 166 226" where the first word is a country name, and the following three numbers are estimated populations of this country in 1900, 2008, and 2025, into a new string with only the first and last words, i.e. "Pakistan 226".
China 1,458
India 1,398
United-States 352
Indonesia 273
Brazil 223
Pakistan 226
Bangladesh 198
Nigeria 208
Russia 137
Japan 126