python dataframe gropuby using pd Series mode throws error when by column contains values with same

Introduction:
Error Scenario:
In this case, the error might look like:
Explanation:
The error occurs because when Pandas tries to find the mode within each group, it encounters values with similar starting characters ('apple' and 'apricot'), leading to a conflict in the mode calculation.
Solution:
To handle this issue, we can create a custom aggregation function that finds the mode using a different approach. We can utilize the value_counts() function to count the occurrences of each value within a group and then select the most frequent one.
This will output:
Now, the custom mode function successfully handles the situation where values have similar starting characters within the 'category' column.
Conclusion:
ChatGPT
Pandas is a powerful data manipulation library in Python, and one of its key features is the ability to group data using the groupby function. However, when using the mode() function on a grouped DataFrame with a column containing values that start with the same sequence, you might encounter unexpected errors. This tutorial will guide you through the issue and provide solutions.
The groupby operation is used to split the data into groups based on some criteria, perform a function on each group independently, and then combine the results. The mode() function, when applied to a Pandas Series, returns the most frequent