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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.

Deze oefening maakt deel uit van de cursus

Big Data Fundamentals with PySpark

Cursus bekijken

Oefeninstructies

  • Print the first 10 observations in the people_df DataFrame.
  • Count the number of rows in the people_df DataFrame.
  • How many columns does people_df DataFrame have and what are their names?

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# 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.____))
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