Locate first and last non-NaN values in a Pandas DataFrame

Question

I have a Pandas DataFrame indexed by date. There a number of columns but many columns are only populated for part of the time series. I'd like to find where the first and last values non-NaN values are located so that I can extract the dates and see how long the time series is for a particular column.

Could somebody point me in the right direction as to how I could go about doing something like this? Thanks in advance.

Answer 1

You can return the first and last non-NaN values by using the Series.first_valid_index and Series.last_valid_index, respectively.

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