get_frequency_summary

get_frequency_summary(idx, force_regular=False, engine='pandas')

More robust version of pandas inferred frequency.

Parameters

Name	Type	Description	Default
`idx`	pd.Series or pd.DateTimeIndex	The `idx` parameter is either a `pd.Series` or a `pd.DateTimeIndex`. It represents the index of a pandas DataFrame or Series, which contains datetime values.	required
`force_regular`	bool	The `force_regular` parameter is a boolean flag that determines whether to force the frequency to be regular. If set to `True`, the function will convert irregular frequencies to their regular counterparts. For example, if the inferred frequency is ‘B’ (business days), it will be converted to ‘D’ (calendar days). The default value is `False`.	`False`

Returns

Type Description

pd.DataFrame A pandas DataFrame with the following columns: - freq_inferred_unit: The inferred frequency of the time series from pandas. - freq_median_timedelta: The median time difference between consecutive observations in the time series. - freq_median_scale: The median time difference between consecutive observations in the time series, scaled to a common unit. - freq_median_unit: The unit of the median time difference between consecutive observations in the time series.

Type	Description
pd.DataFrame	A pandas DataFrame with the following columns: - `freq_inferred_unit`: The inferred frequency of the time series from `pandas`. - `freq_median_timedelta`: The median time difference between consecutive observations in the time series. - `freq_median_scale`: The median time difference between consecutive observations in the time series, scaled to a common unit. - `freq_median_unit`: The unit of the median time difference between consecutive observations in the time series.

Examples

import pytimetk as tk
import pandas as pd
    
dates = pd.date_range(start = '2020-01-01', end = '2020-01-10', freq = 'D')
    
tk.get_frequency_summary(dates)

	freq_inferred_unit	freq_median_timedelta	freq_median_scale	freq_median_unit
0	D	1 days	1.0	D

# pandas inferred frequency fails
dates = pd.to_datetime(["2021-01-01", "2021-02-01"])
    
# Returns None
dates.inferred_freq == None
    
# Returns '1MS'
tk.get_frequency_summary(dates)

	freq_inferred_unit	freq_median_timedelta	freq_median_scale	freq_median_unit
0	None	31 days	1.0	M