Locate first and last non NaN values in a Pandas DataFrame

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 extracts 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.

Bprodz

Answer

@behzad.nouri's solution worked perfectly to return the first and last non-NaN values using Series.first_valid_index and Series.last_valid_index, respectively.

Source (Stackoverflow)

http://stackoverflow.com/questions/22403469/locate-first-and-last-non-nan-values-in-a-pandas-dataframe

Locate first and last non NaN values in a Pandas DataFrame

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