Times and dates in Pandas
summary
Pandas converts messy timestamp text into real datetime64 and timedelta64 types using pd.to_datetime, and can parse on import with read_csv parse_dates or the faster pyarrow engine; timezone work uses tz_localize and tz_convert. The talk demos dt accessor, grouping and pivoting, Grouper and resample, and building a trip_time column by subtracting dropoff minus pickup. Surprising concrete results include four trips longer than three days and one costing $4,268 for about 1.5 miles.
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chapters (15)
- 0:00Introduction
- 1:05Time and datetime objects
- 5:00CSV with datetime columns
- 8:09Parsing datetime strings
- 10:15Aggregating datetime values
- 13:03DT accessor components
- 15:28Trip durations with Time Delta
- 19:00Time zones in datetime
- 21:48Group by datetime
- 24:59Pivot tables with datetime
- 26:46Chronological grouping
- 28:12Datetime to index
- 32:44Resampling time series
- 35:16Datetime functionality summary
- 36:01Q&A
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