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Pandas: Data Manipulation - bdate_range() function

bdate_range() function

The bdate_range() function is used to concatenate pandas objects along a particular axis with optional set logic along the other axes.

Syntax:

pandas.bdate_range(start=None, end=None, periods=None, freq='B', tz=None, normalize=True, name=None, weekmask=None, holidays=None, closed=None, **kwargs)

Parameters:

Name Description Type / Default Value Required / Optional
start  Left bound for generating dates. string or datetime-like
Default Value: None
Required
end  Right bound for generating dates. string or datetime-like
Default Value: None
Required
periods Number of periods to generate. integer
Default Value: None
Required
freq Frequency strings can have multiples, e.g. ‘5H’. string or DateOffset
Default Value: ‘B’ (business daily)
Required
tz Time zone name for returning localized DatetimeIndex, for example Asia/Beijing. string or None Required
normalize Normalize start/end dates to midnight before generating date range. bool
Default Value: False
Required
name  Name of the resulting DatetimeIndex. string
Default Value: None
Required
weekmask Weekmask of valid business days, passed to numpy.busdaycalendar, only used when custom frequency strings are passed. The default value None is equivalent to ‘Mon Tue Wed Thu Fri’. string or None
Default Value: None
Required
holidays Dates to exclude from the set of valid business days, passed to numpy.busdaycalendar, only used when custom frequency strings are passed. list-like or None
Default Value: None
Required
closed  Make the interval closed with respect to the given frequency to the 'left', 'right’, or both sides (None). string
Default Value: None
Required
**kwargs For compatibility. Has no effect on the result.    

Returns: Datetimeindex

Notes

Of the four parameters: start, end, periods, and freq, exactly three must be specified. Specifying freq is a requirement for bdate_range. Use date_range if specifying freq is not desired.

Example:


Download the Pandas DataFrame Notebooks from here.

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