<filename>14 - Data manipulation with Pandas/chapter 4 - Creating and Visualizing DataFrames/6 - Removing missing values.py
'''
Now that you know there are some missing values in your DataFrame, you have a few options to deal with them. One way is to remove them from the dataset completely. In this exercise, you'll remove missing values by removing all rows that contain missing values.

pandas has been imported as pd and avocados_2016 is available.
'''
# Remove rows with missing values
avocados_complete = avocados_2016.dropna()

# Check if any columns contain missing values
print(avocados_complete.isna().any())