From the course: Data Analysis with Python and Pandas

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Key takeaways

Key takeaways

From the course: Data Analysis with Python and Pandas

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Key takeaways

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- [Instructor] All right, so that concludes our journey through time series data. As you probably learned, time series data and dates and times in Python and Pandas are deceptively complicated, and so, there's a lot more to learn here, but what we really need to know to be effective is that the datetime64 data type lets us work with time series in Pandas. As we saw, the conversion can be deceptively complicated, so use the .to_datetime method to manage errors or explicitly state the datetime format for Pandas to interpret it correctly. I generally suggest trying the typical as type method, but if you do run into problems, that's when we want to use .to_datetime. Use our datetime codes and accessors to format date, and extract date components. There are dozens of options for these, but we really only need to memorize the common parts and formats for most business analysis scenarios. We want to be able to extract our month, our day of week, our year. And we can always reference a…

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