How To Create A Histogram In C

A histogram is a graphical representation illustrating the distribution of numerical data. It displays the frequency or quantity of data points within various intervals known as "bins" or "buckets". Statisticians and data analysts commonly use histograms to understand the distribution of a dataset and identify trends, anomalies, and other distinctive features.

The vertical axis of a histogram displays the frequency or quantity of data points within specific intervals, with the horizontal axis indicating the range of data values segmented into intervals. The width of each interval typically remains consistent, although variations may occur based on the nature of the data and the analyst's choices. The bar's height in the histogram corresponds to the quantity of data points within each interval.

The form of the data distribution, whether it is balanced, skewed, displaying two peaks (bimodal), or exhibiting other patterns, can be identified through histograms. Histograms are also valuable for pinpointing outliers since data points that deviate significantly from the majority will show up as isolated bars at the edges of the histogram.

Histograms prove to be a valuable asset in conducting exploratory data analysis and gaining a deeper understanding of the characteristics of the dataset by offering a visual representation of both the central tendency and spread of the data.

Histogram Graph:

A bar chart is utilized to display data in a histogram, providing a visual representation of various outcomes arranged into vertical columns along the x-axis. The y-axis in the histogram corresponds to the frequency or occurrence count for each column of data, making it a straightforward technique for illustrating data distributions. To further illustrate this concept, consider the following example involving Uncle Bruno's garden, which consists of 30 black cherry trees with varying heights ranging from 61 inches to 87 inches. By categorizing the data into specific height ranges, we can organize the information into a frequency distribution table.

Now, a histogram can be used to display this data. When plotting a histogram, we must ensure no spaces between the bars.

How to Make a Histogram?

The steps below outline the process of generating a histogram using the given dataset:

Step 1: Begin by choosing a measurement scale for the horizontal axis to represent weights.

Step 2: Choose an appropriate scale for the vertical axis representing frequencies.

Next, proceed by utilizing the frequencies associated with each of the designated weights to visually represent them through bars on the graph.

Example: Create a histogram illustrating the frequency distribution table provided, which shows the distribution of weights among 25 students in a classroom.

Steps to draw a histogram:

First, start by adjusting the scale so that 1 unit equals 11 lb along the horizontal axis. It's important to introduce a break or discontinuity on the X-axis to accommodate the fact that the weights in the dataset start at 65 rather than 0.

Step 2: The vertical axis spans frequencies from 4 to 10, and we establish a scale where 1 unit is equivalent to 2.

Step 3: Utilizing the frequencies associated with each of the provided weights, depict the bars that correspond to each weight category.

Frequency Histogram:

A histogram that illustrates the frequencies (the count of occurrences) of the provided data elements is referred to as a frequency histogram. For example, if there are 20 newborn babies in a hospital with ages ranging from youngest to oldest as 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 5, a frequency distribution table like the one below can be utilized to present this data:

Now, this data can be shown using a frequency histogram .

Tips and Tricks on Histogram:

Here are a few crucial points and tricks to remember when using a histogram to visualize any data.

• ✅ When creating a histogram , choose the scale on the vertical axis by looking for the highest integer that divides all the frequencies . If such a number doesn't exist, look for the highest number that splits most frequencies.
• ✅ A graph called a histogram is employed to summarize continuous data.
• ✅ A histogram provides the visual interpretation of continuous data.
• ✅ The scales of the horizontal and vertical axes don't need to begin at 0 .
• ✅ A histogram shouldn't have any spaces between the bars.

Program:

Let's take a simple histogram program in C:

#include <stdio.h>

void print_Histogram ( int *hist, int n );

int main() {

int i, j;

int input value, hist_value=0;

printf("Input number of histogram bar : \n");  

scanf("%d", &inputValue);

int hist[inputValue];

if (inputValue<=10)

{    

printf("Input the values : \n");

for (i = 0; i < inputValue; ++i) {

scanf("%d", &hist_value);     	

if (hist_value>=1 && hist_value<=10)

hist[i] = hist_value;

hist_value=0;

}

int results[10] = {0};

for(j = 0; j < inputValue; j++) {

if ( hist[j] == i){

results[i]++;

}

}

printf("\n");

print_Histogram(hist, inputValue);

}

return 0;

}

void print_Histogram(int *hist, int n) {

printf("\nHistogram:\n");

int i, j;

for (i = 0; i < n; i++) {

for ( j = 0; j < hist[i]; ++j) {

printf("#");

}

printf("\n");

}

}

Output:

Input number of histogram bar : 
Input the values : 

Histogram:
#

Example 2:

#include <stdio.h>

int main() {

// Sample data array

int data[] = {10, 15, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95};

// Determine the number of data points and intervals (bins)

int numDataPoints = sizeof(data) / sizeof(data[0]);

int numBins = 5;

int binWidth = 20;

// Array to store frequency counts for each bin

int frequency[numBins];

for (int i = 0; i < numBins; i++) {

frequency[i] = 0;

}

// Calculate frequencies for each bin

for (int i = 0; i < numDataPoints; i++) {

int binIndex = data[i] / binWidth;

frequency[binIndex]++;

}

// Display the histogram

printf("Histogram:\n");

for (int i = 0; i < numBins; i++) {

printf("%3d - %3d: ", i * binWidth, (i + 1) * binWidth - 1);

for (int j = 0; j < frequency[i]; j++) {

printf("*");

}

printf("\n");

}

return 0;

}

Output:

Input number of histogram bar : 
Input the values : 

Histogram:
#

Applications of histogram:

In various industries, histograms are commonly employed for analyzing and presenting data. Creating histograms in the C programming language is beneficial for supporting applications in the fields of Physics and Engineering.

Histograms are valuable tools for evaluating data in scientific experiments, including particle energies, signal strengths, and material characteristics, assisting in understanding various physical phenomena.

• ✅ Market Analysis:

Marketers leverage histograms to tailor marketing strategies through the examination of consumer preferences, survey findings, and demographic data.

• ✅ Education:

Educators have the option to utilize Histograms to assess the performance of their students on exams, tasks, or quizzes and identify any specific areas where additional assistance may be required.

• ✅ When it comes to Image Processing:

Histograms play a crucial role in image processing tasks such as histogram equalization, thresholding, and enhancing contrast. They provide valuable insights into the distribution of pixel intensity values within an image, aiding in informed decision-making when adjusting these values.

• ✅ Data Analysis and Statistics:

Histograms play a crucial role in analyzing and interpreting the spread of numeric data in statistical analysis and data exploration. They are essential tools used to identify trends, anomalies, and central tendencies within datasets, aiding in decision-making processes.

• ✅ Finance and Economics:

Financial experts utilize histograms to assess different financial metrics and display fluctuations in stock prices.

• ✅ Environmental Science:

Histograms are valuable tools for presenting environmental information, such as levels of pollutants, variations in temperature, and precipitation levels, allowing for trend analysis and informed decision-making.

• ✅ Quality Control and Process Monitoring:

Histograms play a crucial role in analyzing the spread of data in quality assurance and overseeing production processes within the manufacturing sector. Anomalies in distributions could signal potential issues within the manufacturing process.

• ✅ Biomedical Research:

Researchers have the opportunity to uncover patterns in health trends and identify possible risk factors through the utilization of histograms for examining medical information like patient ages, blood pressure measurements, and cholesterol levels.

• ✅ Social Sciences:

Histograms are valuable tools for researchers to visualize and analyze survey data in fields such as sociology and psychology, highlighting trends and connections within the data.

When it comes to creating histograms in C, it's important to acknowledge that manually generating them can consume time and introduce errors. Therefore, the selection of suitable libraries and tools for manipulating and visualizing data is paramount. Exploring options such as Gnuplot or crafting custom routines can enhance the efficiency of generating and displaying histograms.