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Method Chaining
In Method Chaining, solve problems using sequential method calls with clean, readable code. Apply this to filter and sort a DataFrame.
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Easy · Method Chaining core interview pattern
Answer-first summary
In Method Chaining, solve problems using sequential method calls with clean, readable code. Apply this to filter and sort a DataFrame.
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In this problem, method chaining is crucial for filtering and sorting animal data by weight. By applying sequential operations in a clean manner, you’ll be able to extract animals heavier than 100 kilograms and sort them in descending order. This helps improve code clarity while achieving the task requirements.
Problem Statement
You are given a DataFrame of animals with their respective name, species, age, and weight. Your task is to filter the animals that weigh strictly more than 100 kilograms and return their names, sorted by weight in descending order.
Your solution should leverage method chaining, allowing you to chain filtering and sorting operations seamlessly, ensuring the final output contains only the names of animals that satisfy the condition, and ordered as requested.
Examples
Example 1
Input: See original problem statement.
Output: See original problem statement.
DataFrame animals +-------------+--------+ | Column Name | Type | +-------------+--------+ | name | object | | species | object | | age | int | | weight | int | +-------------+--------+
Example 2
Input: DataFrame animals: +----------+---------+-----+--------+ | name | species | age | weight | +----------+---------+-----+--------+ | Tatiana | Snake | 98 | 464 | | Khaled | Giraffe | 50 | 41 | | Alex | Leopard | 6 | 328 | | Jonathan | Monkey | 45 | 463 | | Stefan | Bear | 100 | 50 | | Tommy | Panda | 26 | 349 | +----------+---------+-----+--------+
Output: +----------+ | name | +----------+ | Tatiana | | Jonathan | | Tommy | | Alex | +----------+
All animals weighing more than 100 should be included in the results table. Tatiana's weight is 464, Jonathan's weight is 463, Tommy's weight is 349, and Alex's weight is 328. The results should be sorted in descending order of weight.
Constraints
Solution Approach
Method Chaining for Filtering
Use method chaining to first filter the DataFrame to keep only animals with a weight greater than 100 kilograms. This can be done with a condition applied directly to the DataFrame.
Sorting Data in Descending Order
Next, chain the sort method to arrange the filtered animals by their weight in descending order. This ensures that the heaviest animals appear first.
Extracting Names
Finally, chain the selection of the 'name' column to output only the names of the filtered and sorted animals. This final operation ensures the result matches the required format.
Complexity Analysis
| Metric | Value |
|---|---|
| Time | Depends on the final approach |
| Space | Depends on the final approach |
The time and space complexity will depend on the size of the DataFrame and the efficiency of the filtering and sorting operations. Typically, filtering is O(n) and sorting is O(n log n), where n is the number of rows in the DataFrame.
What Interviewers Usually Probe
- Evaluate the candidate's ability to implement method chaining cleanly and concisely.
- Assess whether the candidate understands the importance of readable and efficient code.
- Check how the candidate handles both filtering and sorting operations in a single, streamlined code flow.
Common Pitfalls or Variants
Common pitfalls
- Failing to apply method chaining properly, leading to overly complex or less readable code.
- Incorrectly ordering the method calls, which may result in unexpected outputs.
- Forgetting to check for edge cases, such as an empty DataFrame or no animals above 100 kilograms.
Follow-up variants
- Introduce additional filtering conditions, such as filtering based on species or age.
- Instead of sorting by weight, sort by another property, like age or name.
- Use a different type of data structure for storing animals, such as a list of dictionaries, to apply method chaining in a different context.
FAQ
What is method chaining in programming?
Method chaining is the process of calling multiple methods in a single statement, where each method operates on the result of the previous method.
How do you filter a DataFrame by weight in method chaining?
You can filter a DataFrame by using the condition df[df['weight'] > 100], which will return only the rows where the weight is greater than 100.
What is the time complexity of sorting a DataFrame?
Sorting a DataFrame has a time complexity of O(n log n), where n is the number of rows in the DataFrame.
How do you ensure that the output is sorted by weight in descending order?
You can sort the DataFrame by using the .sort_values(by='weight', ascending=False) method to sort in descending order based on the weight column.
What are some common mistakes when implementing method chaining?
Some common mistakes include not chaining methods in the correct order, making the code harder to understand, or not accounting for edge cases like empty DataFrames.
Solution
Solution 1
#### Python3
import pandas as pd
def findHeavyAnimals(animals: pd.DataFrame) -> pd.DataFrame:
return animals[animals['weight'] > 100].sort_values('weight', ascending=False)[
['name']
]