Conditional list comprehensions for time-stamped data
Great, you've successfully extracted the data of interest, the time, from a pandas DataFrame! Let's tweak your work further by adding a conditional that further specifies which entries to select.
In this exercise, you will be using a list comprehension to extract the time from time-stamped Twitter data. You will add a conditional expression to the list comprehension so that you only select the times in which entry[17:19] is equal to '19'. The pandas package has been imported as pd and the file 'tweets.csv' has been imported as the df DataFrame for your use.
This exercise is part of the course
Python Toolbox
Exercise instructions
- Extract the column
'created_at'fromdfand assign the result totweet_time. - Create a list comprehension that extracts the time from each row in
tweet_time. Each row is a string that represents a timestamp, and you will access the 12th to 19th characters in the string to extract the time. Useentryas the iterator variable and assign the result totweet_clock_time. Additionally, add a conditional expression that checks whetherentry[17:19]is equal to'19'.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Extract the created_at column from df: tweet_time
tweet_time = ____
# Extract the clock time: tweet_clock_time
tweet_clock_time = [____ for ____ in ____ if ____ == ____]
# Print the extracted times
print(tweet_clock_time)