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C++ Program to Draw Histogram

A histogram is a graphical representation of data that shows the distribution of values in a dataset. In this C++ program, I’ll provide a basic example of how to draw a histogram using asterisks (*) to represent the data. We’ll assume you have a dataset of values, and you want to visualize their distribution.

Here’s a simple C++ program to draw a histogram:

C++
#include <iostream>
#include <vector>

void drawHistogram(const std::vector<int>& data) {
    // Find the maximum value in the dataset to determine the scale
    int max_value = 0;
    for (int value : data) {
        if (value > max_value) {
            max_value = value;
        }
    }

    // Determine the number of asterisks per unit on the scale
    double scale_factor = 40.0 / max_value;

    // Draw the histogram
    for (int i = 1; i <= max_value; i++) {
        std::cout << i << ": ";
        int asterisks_to_draw = static_cast<int>(data[i - 1] * scale_factor);
        for (int j = 0; j < asterisks_to_draw; j++) {
            std::cout << "*";
        }
        std::cout << std::endl;
    }
}

int main() {
    // Sample dataset (you can replace this with your own data)
    std::vector<int> data = {5, 8, 12, 3, 15, 7, 10};

    std::cout << "Histogram:" << std::endl;
    drawHistogram(data);

    return 0;
}

In this program:

  1. We define a drawHistogram function that takes a vector of integers (data) representing your dataset.
  2. We find the maximum value in the dataset to determine the scale for the histogram.
  3. We calculate a scale factor to determine how many asterisks should represent each unit on the scale. In this example, we use 40 asterisks as the maximum width of the histogram.
  4. We iterate through each value in the dataset, calculate the number of asterisks to draw for each value, and print the histogram using asterisks.
  5. In the main function, we provide a sample dataset (data) and call drawHistogram to visualize it.

You can replace the data vector with your own dataset to draw a histogram for your specific data.

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