More Data Cleaning: Missing Data
When you print out the length of the DataFrame intraday, you will notice that a few rows are missing. There will be missing data if there are no trades in a particular one-minute interval. One way to see which rows are missing is to take the difference of two sets: the full set of every minute and the set of the DataFrame index which contains missing rows. After filling in the missing rows, you can convert the index to time of day and then plot the data.
Stocks trade at discrete one-cent increments (although a small percentage of trades occur in between the one-cent increments) rather than at continuous prices, and when you plot the data you should observe that there are long periods when the stock bounces back and forth over a one cent range. This is sometimes referred to as "bid/ask bounce".
This exercise is part of the course
Time Series Analysis in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Notice that some rows are missing
print("If there were no missing rows, there would be 391 rows of minute data")
print("The actual length of the DataFrame is:", len(___))