Extracting data from parquet files

One of the most common ways to ingest data from a source system is by reading data from a file, such as a CSV file. As data has gotten bigger, the need for better file formats has brought about new column-oriented file types, such as parquet files.

In this exercise, you'll practice extracting data from a parquet file.

Deze oefening maakt deel uit van de cursus

ETL and ELT in Python

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Oefeninstructies

Read the parquet file at the path "sales_data.parquet" into a pandas DataFrame.
Check the data types of the DataFrame via print()ing.
Output the shape of the DataFrame, as well as it's head.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

import pandas as pd

# Read the sales data into a DataFrame
sales_data = pd.____("____", engine="fastparquet")

# Check the data type of the columns of the DataFrames
print(sales_data.____)

# Print the shape of the DataFrame, as well as the head
print(sales_data.____)
print(sales_data.____())

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