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.
Cet exercice fait partie du cours
Importing and Managing Financial Data in Python
Instructions
- Read the file
nasdaq-listings.csvintonasdaqwithpd.read_csv(), adding the argumentsna_valuesandparse_datesequal to the appropriate values. You should use'NAN'for missing values, and parse dates in theLast Updatecolumn. - Display and inspect the result using
.head()and.info()to verify that the data has been imported correctly.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Import the data
nasdaq = pd.____('nasdaq-listings.csv', ____='NAN', ____=['Last Update'])
# Display the head of the data
print(nasdaq.____())
# Inspect the data
nasdaq.____()