How can I read data from a Parquet file using Databricks in a Python notebook?
To read data from a Parquet file using Databricks in a Python notebook, you can use the `spark.read.parquet()` function. Here's a simple example:

```python
# Import the SparkSession class
from pyspark.sql import SparkSession

# Create a SparkSession object
spark = SparkSession.builder.appName('ParquetReader').getOrCreate()

# Replace 'path_to_your_parquet_file' with the actual path to your Parquet file
parquet_file_path = 'path_to_your_parquet_file'

# Read the Parquet file
df = spark.read.parquet(parquet_file_path)

# Show the data
df.show()
```

In this example, replace `'path_to_your_parquet_file'` with the actual path to your Parquet file. This could be a local file path on your Databricks workspace, or a path to a file stored in a cloud storage service like AWS S3 or Azure Data Lake Storage.

Remember to install the necessary libraries and set up your Databricks workspace before running this code. For more information on how to do this, refer to the Databricks documentation.