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University of Michigan vía Coursera
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Python Functions, Files, and Dictionaries

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  • Files and CSV Output
    • In week one the video lectures and the Runestone textbook will introduce you to the idea of incorporating files into your programs as an additional source of data. You will learn how to read from a file, write to a file, and how to work with the .csv data format.
  • Dictionaries and Dictionary Accumulation
    • In week two the video lectures and the Runestone textbook will focus on a new data type, dictionaries. You will be introduced to the mechanics of dictionaries and then get practice using them in accumulation patterns, both to build a dictionary using the pattern as well as find the best, or worst, result using the pattern.
  • Functions and Tuples
    • In week three you will be introduced to the construction of functions. Up to this point, you have used functions in the programs before, but have not had a chance to write your own functions, including how to define a function, how to incorporate parameters, how to return data from a function, the local or global scope of variables, and potential side effects that could occur from function execution. Finally, we look at tuples more in depth, and how automatic packing and unpacking of tuples can be used in functions and in for loops.
  • More Iteration and Advanced Functions
    • In week four the video lectures and the Runestone textbook will outline a more advanced iteration mechanism, the while loop. You will be introduced to using it when getting feedback from users, as well as applying it to the turtle module to draw images. Additionally, you will also be exposed to more advanced function concepts such as the idea of parameters being optional, not required, and anonymous functions using lambda.
  • Sorting
    • In week five the videos and Runestone textbook will detail how to sort python objects - both the basics and more advanced forms of sorting for dictionaries and how to break a tie (if that occurs). The final course assessment will be a project that asks you to read fake, auto-generated data from a social media site to analyze social media post sentiments. You will submit a csv file as well as images of graphs that demonstrate your findings.