Your chart is full of information. So why does no one know what it means? Sam and Shifra break down everything you need to know about data visualization and storytelling, from picking the right Python library to presenting charts your exec will actually understand. Spoiler: the pie chart doesn't make it out alive. 🌊

We talk about:

• Matplotlib vs Seaborn vs Plotly (and when to use each)
• Declarative vs imperative frameworks and why it matters
• Chart types for EDA: scatterplots, heatmaps, box plots, and pair plots
• Color psychology, colorblindness, and pretty privilege for data
• Why pie charts get so much hate
• The right chart for the right people (Sam's trifecta)
• Chart titles, KISS, and presenting to executives

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Chapters:

0:00 - Charts are communication, not decoration

3:03 - Your Python viz toolkit: Matplotlib, Seaborn, and Plotly

8:15 - Why Seaborn is the beginner's best friend

10:43 - Polars vs. Pandas: Know what your chart is actually for

15:20 - Declarative vs. imperative frameworks (and why it matters)

20:29 - The chart type lineup: Scatterplots, heatmaps, and box plots

28:36 - Pair plots: The boss of all plots

31:31 - Pretty privilege for data: Color, accessibility, and design language

40:22 - Why pie charts are everyone's villain (for good reason)

41:24 - The trifecta: Right people, right info, right chart

46:47 - KISS, chart titles, and presenting to executives

51:49 - Building dashboards people actually use