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# Public Holidays Dataset

> Access worldwide public holiday data covering 38 countries from 1970 to 2099 in Azure Open Datasets.

# Public Holidays Dataset

Worldwide public holiday data sourced from PyPI holidays package and Wikipedia, covering 38 countries or regions from 1970 to 2099.

Each row indicates the holiday info for a specific date, country or region, and whether most people have paid time off.

## Dataset Details

### Volume and Retention

* **Format**: Parquet
* **Size**: Approximately 500KB
* **Date Range**: January 1, 1970 to January 1, 2099
* **Records**: 20,665+ unique dates across 38 countries

### Storage Location

This dataset is stored in the **East US** Azure region. We recommend locating compute resources in East US for affinity.

### Data Sources

This dataset combines data from:

* [Wikipedia](https://en.wikipedia.org/wiki/Category:Lists_of_public_holidays_by_country) (WikiMedia Foundation Inc)
* [PyPI holidays package](https://pypi.org/project/holidays/)

### License

The combined dataset is provided under the [Creative Commons Attribution-ShareAlike 3.0 Unported License](https://en.wikipedia.org/wiki/Wikipedia:Text_of_Creative_Commons_Attribution-ShareAlike_3.0_Unported_License).

## Schema

| Column Name            | Data Type | Description                                                               | Example Values        |
| ---------------------- | --------- | ------------------------------------------------------------------------- | --------------------- |
| `countryOrRegion`      | string    | Country or region full name                                               | Sweden, Norway        |
| `countryRegionCode`    | string    | Country or region code (ISO format)                                       | SE, NO                |
| `date`                 | timestamp | Date of the holiday                                                       | 2025-12-25 00:00:00   |
| `holidayName`          | string    | Full name of the holiday                                                  | Søndag, Christmas Day |
| `isPaidTimeOff`        | boolean   | Whether most people have paid time off (available for US, GB, India only) | True, False, NULL     |
| `normalizeHolidayName` | string    | Normalized name of the holiday                                            | Christmas, New Year   |

<Note>
  The `isPaidTimeOff` column is only available for the United States, Great Britain, and India. For other countries, this field will be NULL.
</Note>

## Preview Data

| countryOrRegion | holidayName        | normalizeHolidayName | countryRegionCode | date       |
| --------------- | ------------------ | -------------------- | ----------------- | ---------- |
| Norway          | Søndag             | Søndag               | NO                | 12/28/2098 |
| Sweden          | Söndag             | Söndag               | SE                | 12/28/2098 |
| Australia       | Boxing Day         | Boxing Day           | AU                | 12/26/2098 |
| Hungary         | Karácsony másnapja | Karácsony másnapja   | HU                | 12/26/2098 |
| Austria         | Stefanitag         | Stefanitag           | AT                | 12/26/2098 |
| Canada          | Boxing Day         | Boxing Day           | CA                | 12/26/2098 |
| Croatia         | Sveti Stjepan      | Sveti Stjepan        | HR                | 12/26/2098 |
| Czech           | 2. svátek vánoční  | 2. svátek vánoční    | CZ                | 12/26/2098 |

## Data Access

### Python SDK (azureml-opendatasets)

Access the dataset using the Azure ML Open Datasets SDK:

```python theme={null}
from azureml.opendatasets import PublicHolidays
from datetime import datetime
from dateutil.relativedelta import relativedelta

# Get holidays from the last month
end_date = datetime.today()
start_date = datetime.today() - relativedelta(months=1)

hol = PublicHolidays(start_date=start_date, end_date=end_date)
hol_df = hol.to_pandas_dataframe()

# Display dataset info
print(hol_df.info())
print(hol_df.head())
```

### Azure Storage (Direct Access)

Access the dataset directly from Azure Blob Storage:

```python theme={null}
import pandas as pd
import sys

# Install required packages
!{sys.executable} -m pip install azure-storage-blob pyarrow pandas

from azure.storage.blob import BlobServiceClient, ContainerClient
import os

# Azure storage configuration
azure_storage_account_name = "azureopendatastorage"
container_name = "holidaydatacontainer"
folder_name = "Processed"

# Create blob service client
container_url = f"https://{azure_storage_account_name}.blob.core.windows.net/"
blob_service_client = BlobServiceClient(container_url)

container_client = blob_service_client.get_container_client(container_name)
blobs = container_client.list_blobs(folder_name)

# Find the latest parquet file
sorted_blobs = sorted(list(blobs), key=lambda e: e.name, reverse=True)
for blob in sorted_blobs:
    if blob.name.startswith(folder_name) and blob.name.endswith('.parquet'):
        target_blob_name = blob.name
        break

print(f'Downloading: {target_blob_name}')

# Download and read the parquet file
_, filename = os.path.split(target_blob_name)
blob_client = container_client.get_blob_client(target_blob_name)
with open(filename, 'wb') as local_file:
    blob_client.download_blob().readinto(local_file)

# Read into pandas DataFrame
df = pd.read_parquet(filename)
print(df.head())
```

### Azure Databricks (Python SDK)

```python theme={null}
# Install in Databricks cluster first:
# pip install azureml-opendatasets

from azureml.opendatasets import PublicHolidays
from datetime import datetime
from dateutil.relativedelta import relativedelta

end_date = datetime.today()
start_date = datetime.today() - relativedelta(months=1)

hol = PublicHolidays(start_date=start_date, end_date=end_date)
hol_df = hol.to_spark_dataframe()

display(hol_df.limit(5))
```

### Azure Databricks (PySpark)

```python theme={null}
# Azure storage access configuration
blob_account_name = "azureopendatastorage"
blob_container_name = "holidaydatacontainer"
blob_relative_path = "Processed"

# Configure SPARK to read from Blob storage
wasbs_path = f"wasbs://{blob_container_name}@{blob_account_name}.blob.core.windows.net/{blob_relative_path}"
print(f'Remote blob path: {wasbs_path}')

# Read parquet files
df = spark.read.parquet(wasbs_path)
print('Register the DataFrame as a SQL temporary view: source')
df.createOrReplaceTempView('source')

# Display top 10 rows
print('Displaying top 10 rows:')
display(spark.sql('SELECT * FROM source LIMIT 10'))
```

### Azure Synapse Analytics

```python theme={null}
# Using azureml-opendatasets in Synapse
from azureml.opendatasets import PublicHolidays
from datetime import datetime
from dateutil.relativedelta import relativedelta

end_date = datetime.today()
start_date = datetime.today() - relativedelta(months=1)

hol = PublicHolidays(start_date=start_date, end_date=end_date)
hol_df = hol.to_spark_dataframe()

# Display top 5 rows
display(hol_df.limit(5))
```

## Use Cases

<AccordionGroup>
  <Accordion title="Demand Forecasting">
    Incorporate holiday information into demand forecasting models to account for seasonal variations and holiday effects on consumer behavior.
  </Accordion>

  <Accordion title="Resource Planning">
    Plan staffing and resource allocation around public holidays across different countries for global operations.
  </Accordion>

  <Accordion title="Calendar Applications">
    Build calendar applications that display public holidays for multiple countries and regions.
  </Accordion>

  <Accordion title="Business Intelligence">
    Analyze business metrics with holiday context to understand performance patterns during holiday periods.
  </Accordion>

  <Accordion title="Travel Planning">
    Help travelers and tourism applications identify public holidays in destination countries.
  </Accordion>
</AccordionGroup>

## Example Analysis

### Count Holidays by Country

```python theme={null}
import pandas as pd
from azureml.opendatasets import PublicHolidays
from datetime import datetime

# Get holidays for 2024
start_date = datetime(2024, 1, 1)
end_date = datetime(2024, 12, 31)

hol = PublicHolidays(start_date=start_date, end_date=end_date)
hol_df = hol.to_pandas_dataframe()

# Count holidays by country
holiday_counts = hol_df.groupby('countryOrRegion')['holidayName'].count().sort_values(ascending=False)
print("\nTop 10 countries by number of holidays:")
print(holiday_counts.head(10))
```

### Find Holidays on Specific Date

```python theme={null}
# Find all countries with holidays on December 25, 2024
christmas_date = pd.Timestamp('2024-12-25')
christmas_holidays = hol_df[hol_df['date'] == christmas_date]

print(f"\nCountries celebrating holidays on {christmas_date.date()}:")
print(christmas_holidays[['countryOrRegion', 'holidayName']].to_string(index=False))
```

### Filter Paid Time Off Holidays

```python theme={null}
# Get only holidays with paid time off in the US
us_paid_holidays = hol_df[
    (hol_df['countryRegionCode'] == 'US') & 
    (hol_df['isPaidTimeOff'] == True)
]

print("\nUS Federal Holidays with Paid Time Off:")
print(us_paid_holidays[['date', 'holidayName']].to_string(index=False))
```

## Supported Countries

The dataset covers 38 countries and regions including:

* Australia, Austria, Canada, Croatia, Czech Republic
* Denmark, Finland, France, Germany, Hungary
* India, Ireland, Italy, Japan, Mexico
* Netherlands, New Zealand, Norway, Poland, Portugal
* Spain, Sweden, Switzerland, United Kingdom, United States
* And more...

## Data Quality Notes

<Warning>
  The `isPaidTimeOff` field is only populated for the United States, Great Britain, and India. For all other countries, this field will be NULL.
</Warning>

<Info>
  Holiday names are provided in the local language of each country. Use the `normalizeHolidayName` field for a more standardized representation where available.
</Info>

## Next Steps

<CardGroup cols={2}>
  <Card title="Create ML Dataset" icon="plus" href="/open-datasets/how-to/create-dataset">
    Learn how to create Azure ML datasets from this data
  </Card>

  <Card title="Browse Catalog" icon="book" href="/open-datasets/catalog">
    Explore other available datasets
  </Card>

  <Card title="COVID-19 Data" icon="virus" href="/open-datasets/datasets/covid-19">
    View COVID-19 tracking datasets
  </Card>

  <Card title="Genomics Data" icon="dna" href="/open-datasets/datasets/genomics">
    Explore genomics datasets
  </Card>
</CardGroup>

## Contact

For questions about this dataset, email [aod@microsoft.com](mailto:aod@microsoft.com).