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  3. Machine Learning for Time Series Data in Python

Exercise

Visualizing messy data

Let's take a look at a new dataset - this one is a bit less-clean than what you've seen before.

As always, you'll first start by visualizing the raw data. Take a close look and try to find datapoints that could be problematic for fitting models.

The data has been loaded into a DataFrame called prices.

Instructions

100 XP
  • Visualize the time series data using Pandas.
  • Calculate the number of missing values in each time series. Note any irregularities that you can see. What do you think they are?