Read data using .read_csv() with adequate parsing arguments

You have successfully identified the issues you must address when importing the given csv file.

In this exercise, you will once again load the NASDAQ data into a pandas DataFrame, but with a more robust function. pandas has been imported as pd.

This exercise is part of the course

Importing and Managing Financial Data in Python

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Exercise instructions

Read the file nasdaq-listings.csv into nasdaq with pd.read_csv(), adding the arguments na_values and parse_dates equal to the appropriate values. You should use 'NAN' for missing values, and parse dates in the Last Update column.
Display and inspect the result using .head() and .info() to verify that the data has been imported correctly.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import the data
nasdaq = pd.____('nasdaq-listings.csv', ____='NAN', ____=['Last Update'])

# Display the head of the data
print(nasdaq.____())

# Inspect the data
nasdaq.____()

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