> ## Documentation Index > Fetch the complete documentation index at: https://mintlify.com/MicrosoftDocs/azure-ai-docs/llms.txt > Use this file to discover all available pages before exploring further. # Bing COVID-19 Dataset > Access daily updated COVID-19 data including confirmed, fatal, and recovered cases from all regions worldwide. # Bing COVID-19 Dataset Bing COVID-19 data includes confirmed, fatal, and recovered cases from all regions, updated daily. The [Bing COVID-19 Tracker](https://bing.com/covid) reflects this data. ## Data Sources Bing collects data from multiple trusted, reliable sources, including: * [BNO News](https://bnonews.com/index.php/2020/04/the-latest-coronavirus-cases/) * [Centers for Disease Control and Prevention (CDC)](https://www.cdc.gov/covid/index.html) * National/regional and state public health departments * [Wikipedia](https://en.wikipedia.org/wiki/2019%E2%80%9320_coronavirus_pandemic) * [World Health Organization (WHO)](https://www.who.int/emergencies/diseases/novel-coronavirus-2019) * [24/7 Wall St.](https://247wallst.com/) ## Dataset Information ### Available Formats Modified Bing COVID-19 datasets are available in multiple formats: * [CSV](https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/bing_covid-19_data/latest/bing_covid-19_data.csv) (560.3 MB) * [JSON](https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/bing_covid-19_data/latest/bing_covid-19_data.json) (1515.6 MB) * [JSON-Lines](https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/bing_covid-19_data/latest/bing_covid-19_data.jsonl) (1506.2 MB) * [Parquet](https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/bing_covid-19_data/latest/bing_covid-19_data.parquet) (55.4 MB) All modified datasets have ISO 3166 subdivision codes and load times added. They use lowercase column names with underscore separators. [CSV-format raw data](https://pandemicdatalake.blob.core.windows.net/public/raw/covid-19/bing_covid-19_data/latest/Bing-COVID19-Data.csv) is also available. ### Data Volume * **Total Records**: 4,766,737+ rows (as of March 5, 2023) * **Update Frequency**: Daily * **Historical Data**: Earlier versions available on [GitHub](https://github.com/microsoft/Bing-COVID-19-Data/commits/) ## Schema | Column Name | Data Type | Description | Example Values | | ------------------ | --------- | ------------------------------------------- | -------------------- | | `id` | int | Unique identifier | 742546, 69019298 | | `updated` | date | The as-of date for the record | 2021-04-23 | | `confirmed` | int | Confirmed case count for the region | 1, 2, 1000 | | `confirmed_change` | int | Change in confirmed cases from previous day | 1, 2, 50 | | `deaths` | int | Death case count for the region | 1, 2, 100 | | `deaths_change` | smallint | Change in deaths from previous day | 1, 2, 5 | | `recovered` | int | Recovered count for the region | 1, 2, 500 | | `recovered_change` | int | Change in recovered cases from previous day | 1, 2, 25 | | `country_region` | string | Country/region | United States, India | | `admin_region_1` | string | Region within country\_region | Texas, Georgia | | `admin_region_2` | string | Region within admin\_region\_1 | Washington County | | `iso2` | string | 2-letter country code identifier | US, IN | | `iso3` | string | 3-letter country code identifier | USA, IND | | `iso_subdivision` | string | Two-part ISO subdivision code | US-TX, US-GA | | `latitude` | double | Latitude of the region centroid | 42.28708, 19.59852 | | `longitude` | double | Longitude of the region centroid | -2.5396, -155.5186 | | `load_time` | timestamp | Date and time file was loaded from source | 2021-04-26 00:06:34 | ## Preview Data | id | updated | confirmed | deaths | country\_region | admin\_region\_1 | confirmed\_change | deaths\_change | | ------ | ---------- | --------- | ------ | --------------- | ---------------- | ----------------- | -------------- | | 338995 | 2020-01-21 | 262 | 0 | Worldwide | null | - | - | | 338996 | 2020-01-22 | 313 | 0 | Worldwide | null | 51 | 0 | | 338997 | 2020-01-23 | 578 | 0 | Worldwide | null | 265 | 0 | | 338998 | 2020-01-24 | 841 | 0 | Worldwide | null | 263 | 0 | | 338999 | 2020-01-25 | 1320 | 0 | Worldwide | null | 479 | 0 | | 339000 | 2020-01-26 | 2014 | 0 | Worldwide | null | 694 | 0 | | 339001 | 2020-01-27 | 2798 | 0 | Worldwide | null | 784 | 0 | | 339002 | 2020-01-28 | 4593 | 0 | Worldwide | null | 1795 | 0 | ## Data Access ### Python (Pandas Direct Access) Download and analyze the dataset using pandas: ```python theme={null} import pandas as pd import numpy as np import matplotlib.pyplot as plt # Read directly from Azure Blob Storage df = pd.read_parquet( "https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/bing_covid-19_data/latest/bing_covid-19_data.parquet" ) print(df.head(10)) print(df.dtypes) ``` ### Analyze Worldwide Data ```python theme={null} # Filter worldwide data df_worldwide = df[df['country_region'] == 'Worldwide'] # Create pivot table df_worldwide_pivot = df_worldwide.pivot_table( df_worldwide, index=['country_region', 'updated'] ) print(df_worldwide_pivot) ``` ### Visualize Trends ```python theme={null} # Plot confirmed cases over time df_worldwide.plot( kind='line', x='updated', y='confirmed', grid=True, title='Worldwide Confirmed COVID-19 Cases' ) # Plot deaths over time df_worldwide.plot( kind='line', x='updated', y='deaths', grid=True, title='Worldwide COVID-19 Deaths' ) # Plot daily change in confirmed cases df_worldwide.plot( kind='line', x='updated', y='confirmed_change', grid=True, title='Daily Change in Confirmed Cases' ) plt.show() ``` ### Azure Databricks (PySpark) Access the dataset in Azure Databricks: ```python theme={null} # Azure storage access configuration blob_account_name = "pandemicdatalake" blob_container_name = "public" blob_relative_path = "curated/covid-19/bing_covid-19_data/latest/bing_covid-19_data.parquet" # Configure SPARK to read from Blob remotely 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 file df = spark.read.parquet(wasbs_path) df.createOrReplaceTempView('covid_data') # Display top 10 rows print('Displaying top 10 rows:') display(spark.sql('SELECT * FROM covid_data LIMIT 10')) ``` ### Azure Synapse Analytics ```python theme={null} # Azure storage access configuration blob_account_name = "pandemicdatalake" blob_container_name = "public" blob_relative_path = "curated/covid-19/bing_covid-19_data/latest/bing_covid-19_data.parquet" # Configure SPARK to read from Blob remotely 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 file df = spark.read.parquet(wasbs_path) df.createOrReplaceTempView('source') # Display top 10 rows display(spark.sql('SELECT * FROM source LIMIT 10')) ``` ## Analysis Examples ### Query Specific Country Data ```python theme={null} import pandas as pd df = pd.read_parquet( "https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/bing_covid-19_data/latest/bing_covid-19_data.parquet" ) # Filter for a specific country us_data = df[df['country_region'] == 'United States'] # Get latest data by state latest_date = us_data['updated'].max() latest_by_state = us_data[ us_data['updated'] == latest_date ].groupby('admin_region_1').agg({ 'confirmed': 'sum', 'deaths': 'sum', 'recovered': 'sum' }).sort_values('confirmed', ascending=False) print(f"\nTop 10 US States by Confirmed Cases (as of {latest_date}):") print(latest_by_state.head(10)) ``` ### Calculate Mortality Rate ```python theme={null} # Calculate mortality rate by country latest_global = df[df['updated'] == df['updated'].max()].copy() latest_global['mortality_rate'] = ( latest_global['deaths'] / latest_global['confirmed'] * 100 ).round(2) top_countries = latest_global[ latest_global['confirmed'] > 1000000 ].sort_values('mortality_rate', ascending=False) print("\nCountries with >1M cases - Mortality Rates:") print(top_countries[['country_region', 'confirmed', 'deaths', 'mortality_rate']].head(10)) ``` ### Time Series Analysis ```python theme={null} # Analyze 7-day moving average of new cases us_nationwide = df[ (df['country_region'] == 'United States') & (df['admin_region_1'].isna()) ].sort_values('updated') us_nationwide['7day_avg_cases'] = us_nationwide['confirmed_change'].rolling(window=7).mean() us_nationwide['7day_avg_deaths'] = us_nationwide['deaths_change'].rolling(window=7).mean() # Plot 7-day moving averages import matplotlib.pyplot as plt fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 8)) ax1.plot(us_nationwide['updated'], us_nationwide['7day_avg_cases']) ax1.set_title('US COVID-19: 7-Day Moving Average of New Cases') ax1.set_ylabel('Cases') ax1.grid(True) ax2.plot(us_nationwide['updated'], us_nationwide['7day_avg_deaths']) ax2.set_title('US COVID-19: 7-Day Moving Average of Deaths') ax2.set_ylabel('Deaths') ax2.set_xlabel('Date') ax2.grid(True) plt.tight_layout() plt.show() ``` ## License and Attribution The data is available strictly for educational and academic purposes under [these terms and conditions](https://github.com/microsoft/Bing-COVID-19-Data/blob/master/LICENSE.txt). ### Valid Use Cases: * Academic institutions * Government agencies * Medical research ### Attribution Requirement: Data used or cited in publications should include an attribution to **"Bing COVID-19 Tracker"** with a link to [www.bing.com/covid](https://www.bing.com/covid). This dataset is for educational and research purposes only. Always verify critical health information with official sources. ## Related Datasets Access additional COVID-19 datasets covering testing, hospital capacity, and mobility European Centre for Disease Prevention and Control COVID-19 data US state-level testing and outcome data Government policy responses to COVID-19 ## Next Steps Learn how to create Azure ML datasets from this data Explore other available datasets View public holidays dataset Explore genomics datasets ## Contact For questions or feedback about this or other datasets in the COVID-19 Data Lake, contact [askcovid19dl@microsoft.com](mailto:askcovid19dl@microsoft.com).