Bird
Raised Fist0
Matplotlibdata~5 mins

Cumulative histograms in Matplotlib - Cheat Sheet & Quick Revision

Choose your learning style10 modes available
Recall & Review
beginner
What is a cumulative histogram?
A cumulative histogram shows the total count of data points up to each bin. It adds counts from previous bins to the current one, helping us see how data accumulates.
Click to reveal answer
beginner
How do you create a cumulative histogram in matplotlib?
Use the parameter cumulative=True in the hist() function to make the histogram cumulative.
Click to reveal answer
beginner
What does the bins parameter control in a histogram?
The bins parameter controls how many intervals the data is split into. More bins mean finer detail, fewer bins mean more general view.
Click to reveal answer
intermediate
Why use a cumulative histogram instead of a regular histogram?
A cumulative histogram helps understand the proportion or count of data below a certain value, showing how data builds up across bins.
Click to reveal answer
intermediate
What does the density=True option do in a histogram?
It normalizes the histogram so the area sums to 1, showing probabilities instead of counts. This works with cumulative histograms to show cumulative probabilities.
Click to reveal answer
Which parameter makes a histogram cumulative in matplotlib?
Acumulative=True
Bdensity=True
Cbins=10
Dstacked=True
What does a cumulative histogram show?
AMaximum value per bin
BOnly counts in each bin
CCounts added up to each bin
DAverage value per bin
If you want to see the probability distribution in a cumulative histogram, which parameter should you use?
Abins=5
Bdensity=True
Ccumulative=False
Dstacked=True
What happens if you increase the number of bins in a histogram?
AYou get more detailed intervals
BYou get fewer intervals
CHistogram becomes cumulative
DHistogram shows averages
Which matplotlib function is used to create histograms?
Aplt.scatter()
Bplt.plot()
Cplt.bar()
Dplt.hist()
Explain how to create and interpret a cumulative histogram using matplotlib.
Think about how counts add up across bins and how matplotlib parameters control this.
You got /4 concepts.
    Describe the difference between a regular histogram and a cumulative histogram.
    Focus on what each histogram tells you about the data.
    You got /4 concepts.

      Practice

      (1/5)
      1. What does setting cumulative=true in plt.hist() do to the histogram?
      easy
      A. It shows the total counts accumulated up to each bin.
      B. It changes the histogram to a bar chart.
      C. It normalizes the histogram to show probabilities.
      D. It colors the bars based on their height.

      Solution

      1. Step 1: Understand the cumulative parameter

        Setting cumulative=True in plt.hist() changes the histogram to show accumulated counts.
      2. Step 2: Effect on histogram output

        Instead of showing counts per bin, it shows the sum of counts up to that bin, making the histogram cumulative.
      3. Final Answer:

        It shows the total counts accumulated up to each bin. -> Option A
      4. Quick Check:

        cumulative=True means accumulation [OK]
      Hint: Remember cumulative=True sums counts up to each bin [OK]
      Common Mistakes:
      • Thinking it normalizes the histogram
      • Confusing cumulative with coloring
      • Assuming it changes chart type to bar chart
      2. Which of the following is the correct syntax to create a cumulative histogram of data array data using matplotlib?
      easy
      A. plt.hist(data, cumulative=True)
      B. plt.hist(data, cumulative=0)
      C. plt.hist(data, cumulate=True)
      D. plt.hist(data, cumulative)

      Solution

      1. Step 1: Check correct parameter name and usage

        The correct parameter to make a histogram cumulative is cumulative=True.
      2. Step 2: Validate syntax correctness

        plt.hist(data, cumulative=True) uses the exact correct syntax. plt.hist(data, cumulative=0) uses 0 instead of True (no cumulative effect). plt.hist(data, cumulate=True) misspells the parameter. plt.hist(data, cumulative) is invalid syntax.
      3. Final Answer:

        plt.hist(data, cumulative=True) -> Option A
      4. Quick Check:

        Use cumulative=True exactly [OK]
      Hint: Use cumulative=True exactly for cumulative histograms [OK]
      Common Mistakes:
      • Misspelling 'cumulative' parameter
      • Using cumulative without assignment
      • Using cumulative=0 (disables cumulative)
      3. What will be the output counts of the cumulative histogram bins for data = [1, 2, 2, 3, 4] with bins [1, 2, 3, 4, 5] using plt.hist(data, bins=[1,2,3,4,5], cumulative=True)?
      medium
      A. [0, 1, 3, 5]
      B. [1, 3, 4, 5]
      C. [1, 1, 2, 3]
      D. [1, 2, 3, 4]

      Solution

      1. Step 1: Count data points in each bin

        Bins: [1-2), [2-3), [3-4), [4-5). Counts per bin: 1 in first, 2 in second, 1 in third, 1 in fourth.
      2. Step 2: Calculate cumulative counts

        Cumulative sums: 1, 1+2=3, 3+1=4, 4+1=5.
      3. Final Answer:

        [1, 3, 4, 5] -> Option B
      4. Quick Check:

        Cumulative sums of counts = [1,3,4,5] [OK]
      Hint: Add counts bin by bin for cumulative totals [OK]
      Common Mistakes:
      • Counting bins inclusively instead of half-open
      • Not summing counts cumulatively
      • Miscounting data points per bin
      4. The code below is intended to plot a cumulative histogram but does not produce the expected cumulative effect. What is the error?
      import matplotlib.pyplot as plt
      data = [1,2,2,3,4]
      plt.hist(data, bins=4, cumulative=False)
      plt.show()
      medium
      A. The bins parameter must be a list, not an integer.
      B. plt.show() is missing and must be added.
      C. The parameter cumulative should be set to True, not False.
      D. Data list must be sorted before plotting.

      Solution

      1. Step 1: Identify the cumulative parameter usage

        The code sets cumulative=False, so the histogram is not cumulative.
      2. Step 2: Correct the parameter to get cumulative histogram

        Changing cumulative=False to cumulative=True will produce the cumulative histogram as intended.
      3. Final Answer:

        The parameter cumulative should be set to True, not False. -> Option C
      4. Quick Check:

        cumulative=True needed for cumulative histogram [OK]
      Hint: Set cumulative=True to enable cumulative histogram [OK]
      Common Mistakes:
      • Leaving cumulative=False by mistake
      • Thinking bins must be a list always
      • Believing data must be sorted
      • Forgetting plt.show() (though present here)
      5. You have two datasets: data1 = [1,2,3,4,5] and data2 = [2,3,4,5,6]. You want to plot their cumulative histograms on the same plot to compare their distributions. Which code snippet correctly does this?
      hard
      A. plt.hist([data1, data2], bins=6, cumulative=False, label=['Data1', 'Data2']); plt.legend(); plt.show()
      B. plt.hist(data1 + data2, bins=6, cumulative=True); plt.show()
      C. plt.hist(data1, bins=6); plt.hist(data2, bins=6); plt.show()
      D. plt.hist([data1, data2], bins=6, cumulative=True, label=['Data1', 'Data2'], histtype='step'); plt.legend(); plt.show()

      Solution

      1. Step 1: Understand plotting multiple cumulative histograms

        To compare cumulative histograms, pass both datasets as a list, set cumulative=True, and use histtype='step' for clarity.
      2. Step 2: Check options for correct parameters

        plt.hist([data1, data2], bins=6, cumulative=True, label=['Data1', 'Data2'], histtype='step'); plt.legend(); plt.show() correctly uses plt.hist([data1, data2], bins=6, cumulative=True, label=['Data1', 'Data2'], histtype='step') with legend and show. plt.hist(data1 + data2, bins=6, cumulative=True); plt.show() incorrectly combines the datasets into one histogram. plt.hist(data1, bins=6); plt.hist(data2, bins=6); plt.show() is not cumulative. plt.hist([data1, data2], bins=6, cumulative=False, label=['Data1', 'Data2']); plt.legend(); plt.show() is not cumulative.
      3. Final Answer:

        plt.hist([data1, data2], bins=6, cumulative=True, label=['Data1', 'Data2'], histtype='step'); plt.legend(); plt.show() -> Option D
      4. Quick Check:

        Multiple datasets + cumulative=True + histtype='step' = plt.hist([data1, data2], bins=6, cumulative=True, label=['Data1', 'Data2'], histtype='step'); plt.legend(); plt.show() [OK]
      Hint: Use list of datasets and cumulative=True with histtype='step' [OK]
      Common Mistakes:
      • Combining datasets into a single histogram
      • Forgetting cumulative=True
      • Not using histtype='step' for clear lines
      • Using cumulative=False by mistake
      Recommended

      Ready to prove it?

      Pass the test and this pattern moves unknown strong while earning +1 Grip toward your certificate.

      10 questions~5 mineasy hard