Internal

Overview

A CSV column can be parsed as date with:

df = pd.read_csv("./timeseries.csv", parse_dates=["date"])

This assumes a "2023-10-31" format. If the string format is different there are several options:

df = pd.read_csv("./timeseries.csv", parse_dates=["date"], date_format='%m/%Y/%d')

More details on format: {{Internal| The common timestamp elements are '%Y-%m-%d %H:%M:%S'. For more details on date format, see ?

For more complicated formats, the parsing function can be provided as a named function or a lambda:

def parse_timestamp(s: str):
  ???
df = pd.read_csv("./timeseries.csv", parse_dates=["date"], date_format='%m/%Y/%d')

For more details on timestamp parsing see:

Time, Date, Timestamp in Python