Malformed Mesh Node Addresses

PandasHardSenior level~10 min

Problem

You are given a DataFrame `mesh_pings` (loaded from `mesh_pings.csv`) with columns `ping_id`, `node_address`, and `latency_ms`. Every row is a single ping recorded when a node answered, carrying that node's dotted address.

A **well-formed** address is exactly four numbers joined by dots, where each number is between 0 and 255 and carries no leading zero (`7` is fine, `07` is not). An address is **malformed** if any segment exceeds 255, if any segment has a leading zero, or if it does not have exactly four segments.

For every distinct malformed `node_address`, return it together with `invalid_count` -- the number of ping rows that carried it. Order by `invalid_count` descending, then by `node_address` descending.

Input data

Example rows — the live problem includes the full dataset.

mesh_pings

ping_id	node_address	latency_ms
1	10.20.30.40	12
2	260.5.6.7	30
3	10.20.030.40	12
4	10.20.30.40	12
5	10.20.30	99

Expected output

Your answer should return 3 rows with the columns node_address, invalid_count.

Starter code (Pandas (Python))

import pandas as pd

def find_malformed_nodes(mesh_pings) -> pd.DataFrame:
    # Your code here
    return mesh_pings

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