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Exercise

Customizing your pandas import

The pandas package is great at dealing with many of the issues you will encounter when importing data as a data scientist, such as comments occurring in flat files, empty lines and missing values (NA or NaN). To wrap up this chapter, you're going to import a corrupted copy of the Titanic dataset titanic_corrupt.txt, which contains comments after the character '#', and is tab-delimited.

Key arguments for pd.read_csv() include:

  • sep sets the expected delimiter.
    • You can use ',' for comma-delimited.
    • You can use '\t' for tab-delimited.
  • comment takes characters that comments occur after in the file, indicating that any text starting with these characters should be ignored.
  • na_values takes a list of strings to identify as NA/NaN. By default, some values are already recognized as NA/NaN. Providing this argument will supply additional values.

Instructions

100 XP
  • Complete the arguments of pd.read_csv() to import titanic_corrupt.txt correctly using pandas:
    • sep sets the delimiter to use, and works the same way as np.loadtxt()'s delimiter argument. Note that the file you're importing is tab-delimited.
    • comment takes characters that comments occur after in the file, which in this case is '#'.
    • na_values takes a list of strings to be treated as NA/NaN, in this case the string 'Nothing'.
  • Execute the rest of the code to print the head of the resulting DataFrame and plot the histogram of the 'Age' of passengers aboard the Titanic.