Read Dask DataFrames from Parquet
In Chapter 1, you analyzed some Spotify data, which was split across multiple files to find the top hits of 2005-2020. You did this using the dask.delayed() function and a loop. Let's see how much easier this analysis becomes using Dask DataFrames.
dask.dataframe has been imported for you as dd.
Este ejercicio forma parte del curso
Parallel Programming with Dask in Python
Instrucciones del ejercicio
- Load the Parquet data folder located in
"data/spotify_parquet". - Use the DataFrame's
.nlargest()method to find the top 10 songs by'popularity'. - Convert the delayed object into a pandas DataFrame by computing it.
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
# Read the spotify_parquet folder
df = ____
# Find the 10 most popular songs
top_10_songs = ____
# Convert the delayed result to a pandas DataFrame
top_10_songs_df = ____
print(top_10_songs_df)