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  3. Python Data Science Toolbox (Part 1)

Exercise

Bringing it all together (1)

You've got your first taste of writing your own functions in the previous exercises. You've learned how to add parameters to your own function definitions, return a value or multiple values with tuples, and how to call the functions you've defined.

In this and the following exercise, you will bring together all these concepts and apply them to a simple data science problem. You will load a dataset and develop functionalities to extract simple insights from the data.

For this exercise, your goal is to recall how to load a dataset into a DataFrame. The dataset contains Twitter data and you will iterate over entries in a column to build a dictionary in which the keys are the names of languages and the values are the number of tweets in the given language. The file tweets.csv is available in your current directory.

Be aware that this is real data from Twitter and as such there is always a risk that it may contain profanity or other offensive content (in this exercise, and any following exercises that also use real Twitter data).

Instructions

100 XP
  • Import the pandas package with the alias pd.
  • Import the file 'tweets.csv' using the pandas function read_csv(). Assign the resulting DataFrame to df.
  • Complete the for loop by iterating over col, the 'lang' column in the DataFrame df.
  • Complete the bodies of the if-else statements in the for loop: if the key is in the dictionary langs_count, add 1 to the value corresponding to this key in the dictionary, else add the key to langs_count and set the corresponding value to 1. Use the loop variable entry in your code.