> ## Documentation Index
> Fetch the complete documentation index at: https://nixtla.io/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Date Features
> Use holidays flags and special dates to improve your accuracy
Date features are an essential part of time series analysis. This document introduces helpful classes (CountryHolidays and SpecialDates) for generating holiday flags, custom date markers, and adding them to TimeGPT.
## Overview
Easily attach holiday flags for multiple countries based on a list of countries.
Add flags for custom events or significant dates you define.
These classes help you enrich your time series datasets with relevant date-based signals. Use them alongside standard data preprocessing techniques to enhance your model's understanding of seasonality and special events.
source
#### CountryHolidays
> ```text theme={null}
> CountryHolidays (countries:list[str])
> ```
*Given a list of countries, returns a dataframe with holidays for each
country.*
```python theme={null}
import pandas as pd
```
| | US\_New Year's Day | US\_Memorial Day | US\_Independence Day | US\_Labor Day | US\_Veterans Day | US\_Veterans Day (observed) | US\_Thanksgiving | US\_Christmas Day | US\_Martin Luther King Jr. Day | US\_Washington's Birthday | ... | US\_Juneteenth National Independence Day (observed) | US\_Christmas Day (observed) | MX\_Año Nuevo | MX\_Día de la Constitución | MX\_Natalicio de Benito Juárez | MX\_Día del Trabajo | MX\_Día de la Independencia | MX\_Día de la Revolución | MX\_Transmisión del Poder Ejecutivo Federal | MX\_Navidad |
| ---------- | ------------------ | ---------------- | -------------------- | ------------- | ---------------- | --------------------------- | ---------------- | ----------------- | ------------------------------ | ------------------------- | --- | --------------------------------------------------- | ---------------------------- | ------------- | -------------------------- | ------------------------------ | ------------------- | --------------------------- | ------------------------ | ------------------------------------------- | ----------- |
| 2018-09-03 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2018-09-04 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2018-09-05 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2018-09-06 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2018-09-07 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
```python theme={null}
c_holidays = CountryHolidays(countries=['US', 'MX'])
periods = 365 * 5
dates = pd.date_range(end='2023-09-01', periods=periods)
holidays_df = c_holidays(dates)
holidays_df.head()
```
***
source
#### SpecialDates
> ```text theme={null}
> SpecialDates (special_dates:dict[str,list[str]])
> ```
*Given a dictionary of categories and dates, returns a dataframe with
the special dates.*
```python theme={null}
special_dates = SpecialDates(
special_dates={
'Important Dates': ['2021-02-26', '2020-02-26'],
'Very Important Dates': ['2021-01-26', '2020-01-26', '2019-01-26']
}
)
periods = 365 * 5
dates = pd.date_range(end='2023-09-01', periods=periods)
holidays_df = special_dates(dates)
holidays_df.head()
```
| | Important Dates | Very Important Dates |
| ---------- | --------------- | -------------------- |
| 2018-09-03 | 0 | 0 |
| 2018-09-04 | 0 | 0 |
| 2018-09-05 | 0 | 0 |
| 2018-09-06 | 0 | 0 |
| 2018-09-07 | 0 | 0 |