.md .pdf

repository open issue

Contents

08_Vector_TimeSeries_SNOTEL_prep

Introduction

Static spatial analysis is powerful, but things often vary in time…

Options to represent time in Python

• https://csit.kutztown.edu/~schwesin/fall20/csc223/lectures/Pandas_Time_Series.html

• Multiple options to represent datetime objects - easy to convert

Python datetime

• Built-in module called datetime which contains classes for datetime object (and timedelta object) - can be confusing

• https://docs.python.org/3/library/datetime.html

NumPy datetime64

• https://numpy.org/doc/stable/reference/arrays.datetime.html

Pandas Timestamp

• https://pandas.pydata.org/docs/user_guide/timeseries.html

• https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Timestamp.html

• https://pandas.pydata.org/docs/user_guide/timeseries.html#overview

• DatetimeIndex

• pd.to_datetime()

  • Accepts “int, float, str, datetime, list, tuple, 1-d array, Series, DataFrame/dict-like”

xarray

• https://xarray.pydata.org/en/stable/user-guide/time-series.html

previous

08: Vector time series: SNOTEL data for the Western U.S.

next

08 Demo: Python Time