Pandas: slow date conversion

Note: As @ritchie46’s answer states, this solution may be redundant since pandas version 0.25 per the new argument cache_dates that defaults to True

Try using this function for parsing dates:

def lookup(date_pd_series, format=None):
    """
    This is an extremely fast approach to datetime parsing.
    For large data, the same dates are often repeated. Rather than
    re-parse these, we store all unique dates, parse them, and
    use a lookup to convert all dates.
    """
    dates = {date:pd.to_datetime(date, format=format) for date in date_pd_series.unique()}
    return date_pd_series.map(dates)

Use it like:

df['date-column'] = lookup(df['date-column'], format="%Y%m%d")

Benchmarks:

$ python date-parse.py
to_datetime: 5799 ms
dateutil:    5162 ms
strptime:    1651 ms
manual:       242 ms
lookup:        32 ms

Source: https://github.com/sanand0/benchmarks/tree/master/date-parse