Based on the dataframe generated in practice 1, use Loop to create a new columnnamed Age_Comparison indicating whether the age of a person is higher, lower or the same asthe average age in the dataset. (You can use Higher/Same/Lower).
Question
Based on the dataframe generated in practice 1, use Loop to create a new columnnamed Age_Comparison indicating whether the age of a person is higher, lower or the same asthe average age in the dataset. (You can use Higher/Same/Lower).
Solution
To answer this question, we will use Python and pandas library. Here are the steps:
- First, you need to calculate the average age. You can do this by using the mean() function on the 'age' column of your dataframe. Let's assume your dataframe is named 'df'.
average_age = df['age'].mean()
- Next, you need to create a new column 'Age_Comparison'. You can do this by using a for loop to iterate over the 'age' column. If the age is higher than the average, you will set 'Age_Comparison' to 'Higher'. If it's lower, you will set it to 'Lower'. If it's the same, you will set it to 'Same'.
df['Age_Comparison'] = ['Higher' if i > average_age else 'Lower' if i < average_age else 'Same' for i in df['age']]
This will create a new column 'Age_Comparison' in your dataframe with the values 'Higher', 'Lower', or 'Same' depending on whether the age is higher, lower, or the same as the average age.
Similar Questions
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