Inspecting data in PySpark DataFrame
Inspecting data is very crucial before performing analysis such as plotting, modeling, training etc. In this simple exercise, you'll inspect the data in the people_df DataFrame that you have created in the previous exercise using basic DataFrame operators.
Remember, you already have a SparkSession spark and a DataFrame people_df available in your workspace.
Questo esercizio fa parte del corso
Big Data Fundamentals with PySpark
Istruzioni dell'esercizio
- Print the first 10 observations in the
people_dfDataFrame. - Count the number of rows in the
people_dfDataFrame. - How many columns does
people_dfDataFrame have and what are their names?
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# Print the first 10 observations
people_df.____(10)
# Count the number of rows
print("There are {} rows in the people_df DataFrame.".format(people_df.____()))
# Count the number of columns and print their names
print("There are {} columns in the people_df DataFrame and their names are {}".format(len(people_df.____), people_df.____))