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Count point

As explained in The Well-Grounded Data Analyst

A count point is a physical measurement location where traffic observations are collected.

A count point is a measurement location where traffic observations are collected. Each point defines a separate time series, while the same observations can also be aggregated by region, local authority, or time period. section 8.4.1

Treat the location ID as a key analytical dimension: inspect how many dates each point covers, identify points with only one day of data, and exclude long-running series with gaps when continuous coverage is required. section 8.4.1

Location-level traffic series

For count point 26010, aggregate All_motor_vehicles by Count_date and plot the totals over time to inspect one location's traffic series. section 8.4.1

fig, axis = plt.subplots()

LOCATION_ID = "26010"

(
    traffic
    .query(f"Count_point_id == {LOCATION_ID}")
    .groupby("Count_date")
    ["All_motor_vehicles"]
    .sum()
    .plot(ax=axis)
)

axis.set(
    title=f"Number of vehicles over time (location {LOCATION_ID})",
    xlabel="Date",
    ylabel="Number of vehicles (total)"
)

plt.show()

This listing groups vehicle counts by date for one count point and plots the resulting series. section 8.4.1

How The Well-Grounded Data Analyst covers it

How deep it goes
Develops practical completeness, coverage, and gap checks by count-point ID before constructing annual series.
Examples
Uses location 26010 for a plotted vehicle series and compares single-day locations across regions.
What you can do after
Evaluate/understand whether location-level traffic series have adequate continuous coverage for analysis.
How it connects
Connects count points to time series, aggregation, regions, local authorities, missing data, and data gaps.
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This explainer was generated by Manning's knowledge graph from the text of The Well-Grounded Data Analyst. The section links point to the parts of the book it draws on.