IntermediateEnergyPYTHON+20 XP

Intermediate plus 1: Bar chart with matplotlib

Scenario

You are a data analyst in the Energy team, working with power_readings data. plt.bar draws one bar per group, so you can compare sizes by eye.

Question

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

Your task

Write each line of your code
Press Check my answer
Change one value and check again

matplotlib

Read the simple theory: matplotlib

Intermediate · Record Counting & Average Calculations — question 6 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 notebookmore-da-010.ipynbFileEditViewRunKernel: Python 3

[md]

Intermediate plus 1: Bar chart with matplotlib

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 editorpower_readings

Snippets

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

🌈 In short — no coding words

📂 Opens the "power_readings" 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

power_readings

IndustryDataset size

The tiny starter data. Bigger data scrolls.

Fields

reading_id	plant	megawatts
E1	Solar	40
E2	Wind	55
E3	Solar	35
E4	Hydro	70

Energy 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.

2 left

Uses plt.bar
Adds a title