Resampling changes the time scale of time-indexed data: like sorting events into calendar bins, it groups observations by periods such as days, weeks, months, or years and supports aggregation. section 10.0 section 10.8
Count Apollo missions in six-month periods
After converting the Apollo launch dates and setting Date as the index, use df.resample('6M').count() to produce one count for each six-month period. Numeric time-series data can likewise be summarized with mean or std. section 10.8
Use resampling when the question asks for a summary over recurring time windows:
- Choose a period, such as one day, two weeks, six months, or one year. section 10.8
- Apply an aggregation such as count, mean, or standard deviation. section 10.8
- Check that the data is a time series with a datetime column serving as its index. section 10.17
