Advanced 8: Clean bad values

Scenario

You are a data analyst in the Healthcare team. Skip values that can't become numbers.

Question

Write your code in the editor, press Check my answer, then try changing one small thing.

Your task

Write your code in the editor
Press Check my answer
Look at the result on the right

Data cleaning

Read the simple theory: print

Advanced · Comprehensions & Data Filtering — question 8 of 30

Finish all 30 to earn a certificate

1. Choose your dataset

Pick an industry and a size. Your code and results change to match.

IndustrySize

📓 DataPro notebookpy-basic-474.ipynbFileEditViewRunKernel: Python 3

[md]

Advanced 8: Clean bad values

Write your code in the editor, press Check my answer, then try changing one small thing.

In [1]:

Your code cell is below. Press Check my answer to run the cell — the result appears as Out [1].

python editorclinic_visits

Snippets

💡 Explain my whole code, line by line (hover any word in the editor for a tip)

🌈 In short — no coding words

📂 Opens the "clinic_visits" table→✅ Shows you the answer

Altogether: this script runs top to bottom, one line at a time, building up the answer step by step.

Start typing to see suggestions. Press Enter to use one. Red marks show the line to fix. Drag a bottom corner horizontally and vertically to resize.

Type your code here ↓Tap or click inside the box to start

✍️ Tap here to type

Dataset & schema

clinic_visits

IndustryDataset size

The tiny starter data. Bigger data scrolls.

Fields

visit_id	ward	wait_minutes
V1	Kids	20
V2	Adults	45
V3	Kids	15
V4	Elderly	30

Healthcare data only.

attempts: 0

▶ Output terminal

$ Press “Check my answer” — results appear here.

Your next steps

Each item turns green when your answer includes it.

1 left

Catches ValueError