Lab 8

Data analysis

For this lab you'll use dictionaries to collect statistics for a simple data file representing a collection of users. Begin by downloading the starter code and data hereLinks to an external site.open in new window

In the starter directory, you'll find three files. The users.csv file contains the data itself in comma separated format. Notice that the first line of the file indicates what field each column represents.

The second file to look at is report.py. This file has been written for you. Read it closely and make sure you understand what it is doing and what it needs. It should be clear that it is mainly just outputting the results of the data analysis class, which it imports.

The file data_analysis is where you'll do the work for this lab. You'll need to set up the data analysis object read the file line by line, split the lines appropriately, and tally the relevant statistics. Specifically, you will need to keep counts of how many times each language shows up in a data item, and how many times each 2-letter country top-level domainLinks to an external site.open in new window signifier shows up in an email address. Top-level domains are always the last letters after the last period in an email domain name, and country codes are always exactly 2 letters long. Furthermore you'll calculate frequencies of these events within the context of the full data set.

Reporting the data

Your program should output a summary of the data as follows:

    $ python report.py users.csv
    Languages:
    English:         0.118
    Spanish:         0.105
    Chinese:         0.087
    Hindi:           0.069
    French:          0.054
    Arabic:          0.039
    Russian:         0.038
    Nepali:          0.019
    Polish:          0.017
    Indonesian:      0.016
    Top level country domains:
    jp:      0.04
    uk:      0.029
    ru:      0.025
    cn:      0.019
    de:      0.012
    au:      0.01
    io:      0.008
    cz:      0.008
    fr:      0.007
    pl:      0.007

Implementation

You will need to use dictionaries to keep your tallies, and I encourage to use regular expressions to capture the top-level domain country codes in emails. I recommend using re.findall here because it outputs an easy-to-understand list of strings that match your regular expression, and only includes the portions of the string that were captured by parentheses. Read the documentation for regular expressions (and findall in particular) here: https://docs.python.org/3/library/re.htmlLinks to an external site.open in new window.

Returning a list of dictionary items sorted by values

Dictionaries themselves are (best regarded as) unordered. However, their items may be returned as a list of pairs (tuples) using the .items() method, and lists can be sorted using the sorted() function on lists. However, simply sorting the items won't quite do. By default, the items would be sorted according to the dictionary key, rather than the value; so we'd wind up with the n-grams in alphabetical order, rather than in order of count.

The sorted() function has several optional arguments that can help. The key argument lets us define an anonymous function that takes the item and returns a value; this value is then used as the basis for ordering the list. Since our items here are tuples and the value we want to order by is the second element of the tuple (index 1), the function we define will take x (a tuple) and return x[1] (the second value of the tuple). The syntax for this makes use of the lambda key word, which is used to define anonymous functions in place. So key=lambda x:x[1] will set the key. You also need to set the reverse parameter to True.

Submission

Submit files user_data.zip to Canvas.

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