Generating Synthetic Sales Data

To generate a synthetic dataset using Faker library for the previous 101 visualization examples, we'll create a Python script that generates random data for the specified columns. Since Faker generates random data, keep in mind that this dataset will be artificial and not representative of any real-world data.First, make sure you have installed the Faker library. You can install it using pip:bash...

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Generating Synthetic Dataset with Faker

Installing Faker Librarythe steps to install the Faker library on Windows 10 with Anaconda distribution:• Open Anaconda Prompt: Click on the Windows Start button, type "Anaconda Prompt," and open the Anaconda Prompt application.• Activate Environment (Optional): If you want to install Faker in a specific conda environment, activate that environment using the following command:• conda activate your_environment_name-...

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Installing Required Libraries

To install required Python libraries for data visualization, you can use either pip or conda, depending on your package manager (Anaconda or standard Python distribution). Below are the detailed steps for installing libraries using both methods:• Using pip (Standard Python Distribution):• Step 1: Open a command prompt or terminal on your computer.• Step 2: Ensure that you have Python installed. You...

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Python Libraries for Data Visualization

Python offers a variety of powerful libraries for data visualization that cater to different user needs and preferences. Each library has its strengths and weaknesses, making it important to choose the right one based on the specific visualization requirements. Below are some of the most popular Python libraries for data visualization: • Matplotlib: Matplotlib is one of the oldest and most widely...

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Qualitative Data Visualization

For qualitative data, which represents categories or labels, different visualization types are recommended to effectively communicate insights. Here are some commonly used visualization types and their advantages for qualitative data:Qualitative Data Visualization:• Bar Charts: Bar charts are one of the most common ways to display qualitative data. They show the frequency or count of each category,...

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Choosing the Right Visualizations for Quantitative and Qualitative Data

Data visualization plays a critical role in understanding and communicating insights from data. With the vast amount of information available, choosing the right visualization techniques is essential to effectively represent quantitative and qualitative data. In this post, we explore recommended visualization types for both quantitative and qualitative data, highlighting their strengths and best use...

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Why Data Visualization Matters

Data visualization matters because it is a powerful tool that allows us to comprehend complex data and extract meaningful insights quickly and effectively. Through the use of graphical representations, data visualization transforms raw numbers and statistics into visual patterns, trends, and relationships, making it easier for individuals to understand and interpret the information.Here are the key...

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OpenCV and Image Processing - Histogram for colored Images

The histogram is created on a channel-by-channel basis, a color image has blue, green and red channels. To plot the histogram for color images, the image should be split into blue, green and red channels, and plot the histogram one by one. With matplotlib library we can put the three histograms in one plot. Below is the code to generate histogram for color image:1 def show_histogram_color(image):2...

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OpenCV and Image Processing - Histogram for Grayscale Images

There are two ways to compute and display histograms. First, OpenCV provides cv2.calcHist() function to compute a histogram for an image, second, use matplotlib to plot the histogram diagram, matplotlib is a Python library for creating static, animated, and interactive visualizations.Figure 7 shows...

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OpenCV and Image Processing - Histogram

A histogram is a graphical representation of the distribution of pixel values in an image. In image processing, a histogram can be used to analyze the brightness, contrast, and overall intensity of an image. It is plotted in a x-y chart, the x-axis of a histogram represents the pixel values ranging...

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OpenCV and Image Processing - Blur Image (Median Blur)

Same as Gaussian Blur, the Median Blur is also widely used in image processing, it is often used for noise reduction purposes. Similar to the Gaussian Blur filter, instead of applying Gaussian formula, the Median Blur calculates the median of all the pixels inside the kernel filter and the central pixel...

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