> ## 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

> [!NOTE]
>
> 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

> [card] CountryHolidays
>
> Easily attach holiday flags for multiple countries based on a list of countries.

> [card] SpecialDates
>
> 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](https://github.com/Nixtla/nixtla/blob/main/nixtla/date_features.py#LNone)

#### 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](https://github.com/Nixtla/nixtla/blob/main/nixtla/date_features.py#LNone)

#### 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 |