financialdatapy.date module¶
This module parses and converts objects to date format objects
- financialdatapy.date.validate_date(period: str, start: bool = False) pandas._libs.tslibs.timestamps.Timestamp[source]¶
Validate the format of date passed as a string.
- Parameters
period (str) – Date in string. If None, date of today is assigned.
start (bool, optional) – Whether argument passed is a starting date or an ending date, defaults to False.
- Raises
IntegerDateInputError – If integer type object is passed.
- Returns
Date with format YYYY-MM-DD or YY-MM-DD.
- Return type
pandas.Timestamp
- financialdatapy.date.string_to_date(period: Union[str, datetime.datetime], date_format: str) pandas._libs.tslibs.timestamps.Timestamp[source]¶
Convert date in string format or datetime object to pandas.Timestamp.
- Parameters
period (Union[str, datetime]) – Date object either string or datetime.datetime.
date_format (str) – Date format to convert to.
- Returns
Date in
Pandas.Timestamp.- Return type
pd.Timestamp
- financialdatapy.date.date_to_timestamp(period: pandas._libs.tslibs.timestamps.Timestamp) int[source]¶
Parse date passed in into a timestamp.
- Parameters
period (pandas.Timestamp) – Date object.
- Returns
The timestamp value equivalent to the date passed.
- Return type
int
- financialdatapy.date.convert_date_format(period: pandas._libs.tslibs.timestamps.Timestamp, format: str) str[source]¶
Convert date object to desired date format.
- Parameters
period (pandas.Timestamp) – Date object.
format (str) – Desired date format to convert to.
- Returns
Converted date in string.
- Return type
str