🖥️ Week 02, Day 01 - Lecture

Making Charts Worth Looking At

🥅 Learning Objectives

By the end of the lecture, you should be able to: i) Spot common problems in everyday charts and say what would make the chart clearer, ii) Choose among bar, line, and scatter for a simple claim about tidy data, iii) Build a chart with plotly.express from a DataFrame (not parallel lists), iv) Describe how a table must look before those chart types work, v) Steer an AI toward plotly docs and DataFrame plot code, and write a title that states a finding.

⏰ Monday, 20 July 2026 | 10:00am - 1:00pm 📍 CBG.2.01 (see LSE’s 🗺️ campus map)

Last Thursday you summarised tables with pandas. Today you make charts that state a takeaway, using the London heatwave series as the running example, then shape a table so plotly.express can draw it. Midterm work continues this afternoon.

🗣️ Lecture Overview

• Midterm Q&A: short openers before new content
• Charts worth looking at: DOs and DON’Ts for essential types, a Moodle bad-plot hunt, and an opening look at the plotly gallery
• Coffee break
• Shape the data for plotly.express: DataFrame columns in the call only, reject x/y as parallel lists, plus short tips for steering AI
• Midterm support: open work until lunch

🎬 Lecture Slides

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After the Lecture

This afternoon is chart practice and midterm work time. The lab page and notebook take you from a tidy CSV (then nested JSON) to a plotly.express chart; solutions stay with instructors.

✍️ Midterm

Due tomorrow. Use the afternoon work period.

➡️ Midterm brief

Questions?

Ask your class teacher during the lab.