5.3 Graphs and charts

NCA-GENM · Data Analysis and Visualization (10% of the exam) · Official objective: “Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.”

Histograms, heat maps and cross-filtering dashboards.

Key points

  1. A histogram shows how often values fall in each range. NVIDIA's example used one to show most bike trips were under 20 minutes.

    What NVIDIA says (2)

    “An hvPlot histogram of trip durations generated with the Divvy dataset”

    — Accelerated Data Analytics: A Guide to Data Visualization with RAPIDS

    “In this instance, the vast majority of bike trips appear under 20 minutes.”

    — Accelerated Data Analytics: A Guide to Data Visualization with RAPIDS

  2. hvPlot is a pandas-like plotting API with built-in interactivity.

    What NVIDIA says (1)

    “Charts in hvPlot can be interactively displayed using Bokeh and Plotly extensions, or statically with the Matplotlib extension.”

    — Accelerated Data Analytics: A Guide to Data Visualization with RAPIDS

  3. Cross-filtering means selecting data in one chart filters all linked charts. NCCL means the NVIDIA Collective Communications Library.

    What NVIDIA says (1)

    “cuxfilter enables GPU accelerated cross-filtering dashboards from notebooks, in just a few lines of Python code.”

    — Welcome to cuxfilter’s documentation — cuxfilter 26.06.00 documentation

  4. A heat map colors a grid of two categories by a value. It shows patterns across both at once.

    What NVIDIA says (1)

    “An hvPlot heat map showing trips by hour and day of week, per month”

    — Accelerated Data Analytics: A Guide to Data Visualization with RAPIDS

Key terms

Sample question

You want to see whether most video clips in a dataset are short. Which chart fits?

Show the answer

Answer: A histogram of clip durations

A histogram shows how often values fall in each range. NVIDIA's example used one to show most bike trips were under 20 minutes.

What NVIDIA says (2)

“An hvPlot histogram of trip durations generated with the Divvy dataset”

— Accelerated Data Analytics: A Guide to Data Visualization with RAPIDS

“In this instance, the vast majority of bike trips appear under 20 minutes.”

— Accelerated Data Analytics: A Guide to Data Visualization with RAPIDS

Practice 5.3 (4 questions) Full Data Analysis and Visualization guide

← 5.2 Attention maps · 5.4 Relationships, trends and confounders →