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
Exercise instructions
- Read the file
nasdaq-listings.csv
intonasdaq
withpd.read_csv()
, adding the argumentsna_values
andparse_dates
equal to the appropriate values. You should use'NAN'
for missing values, and parse dates in theLast 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.____()