Bin count and bin edges in Matplotlib - Step-by-Step Execution

Concept Flow - Bin count and bin edges

Start with data array

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Choose number of bins or bin edges

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Calculate bin edges

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Count data points in each bin

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Output bin counts and edges

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End

We start with data, decide bins, calculate edges, count points per bin, then output counts and edges.

Execution Sample

Matplotlib

import numpy as np

values = np.array([1, 2, 2, 3, 4, 5])
counts, edges = np.histogram(values, bins=3)
print(counts)
print(edges)

This code counts how many values fall into 3 bins and shows the bin edges.

Execution Table

Step	Action	Input/Condition	Result
1	Start with data array	values = [1, 2, 2, 3, 4, 5]	Data array ready
2	Choose number of bins	bins = 3	3 bins selected
3	Calculate bin edges	min=1, max=5, bins=3	Edges = [1.0, 2.3333, 3.6667, 5.0]
4	Count data points in bins	Values: 1,2,2,3,4,5	Counts = [3, 1, 2]
5	Output counts and edges	counts, edges	counts=[3,1,2], edges=[1.0,2.3333,3.6667,5.0]
6	End	All steps done	Execution complete

💡 All data points counted in bins, process finished

Variable Tracker

Variable	Start	After Step 3	After Step 4	Final
values	[1,2,2,3,4,5]	[1,2,2,3,4,5]	[1,2,2,3,4,5]	[1,2,2,3,4,5]
bins	Not set	3	3	3
edges	Not set	[1.0, 2.3333, 3.6667, 5.0]	[1.0, 2.3333, 3.6667, 5.0]	[1.0, 2.3333, 3.6667, 5.0]
counts	Not set	Not set	[3, 1, 2]	[3, 1, 2]

Key Moments - 2 Insights

Why are there 4 bin edges for 3 bins?

Because bin edges mark the boundaries between bins, so for N bins there are N+1 edges (see execution_table step 3).

Why does the first bin count include the value 1 but not 2.3333?

Bins include the left edge but exclude the right edge except the last bin includes both edges (see execution_table step 4).

Visual Quiz - 3 Questions

Look at the execution table, what is the bin edge at index 2 after step 3?

A 2.3333

B 5.0

C 3.6667

D 1.0

💡 Hint

Check the 'Calculate bin edges' row in execution_table, column 'Result'

At which step do we get the counts of data points in each bin?

A Step 4

B Step 3

C Step 2

D Step 5

💡 Hint

Look for 'Count data points in bins' action in execution_table

If we increase bins from 3 to 4, how does the counts array length change?

A It becomes length 5

B It becomes length 4

C It stays the same length

D It becomes length 3

💡 Hint

Counts array length equals number of bins (see variable_tracker for counts)

Concept Snapshot

np.histogram(data, bins)
- Returns counts and bin edges
- counts length = bins
- edges length = bins + 1
- bins divide data range evenly by default
- Left edge inclusive, right edge exclusive except last bin

Full Transcript

We start with a data array and decide how many bins to use. Then we calculate the bin edges that split the data range into equal parts. Next, we count how many data points fall into each bin. Finally, we output the counts and edges. For example, with data [1,2,2,3,4,5] and 3 bins, edges are [1.0, 2.3333, 3.6667, 5.0] and counts are [3,1,2]. There are always one more edges than bins. Bins include the left edge but exclude the right edge except the last bin includes both edges.