Efficient summaries
While pandas and NumPy have tons of functions, sometimes, you may need a different function to summarize your data.
The .agg() method allows you to apply your own custom functions to a DataFrame, as well as apply functions to more than one column of a DataFrame at once, making your aggregations super-efficient. For example,
df['column'].agg(function)
In the custom function for this exercise, "IQR" is short for inter-quartile range, which is the 75th percentile minus the 25th percentile. It's an alternative to standard deviation that is helpful if your data contains outliers.
sales is available and pandas is loaded as pd.
This exercise is part of the course
Data Manipulation with pandas
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# A custom IQR function
def iqr(column):
return column.quantile(0.75) - column.quantile(0.25)
# Print IQR of the temperature_c column
print(____)