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    Data visualization is the practice of presenting information in graphical formats, making it easier to interpret and spot patterns. There are various types of data visualization techniques, each suited for different data types and analysis goals.

    Basic Charts for Data Visualization

    Bar Charts: Bar charts use rectangular bars to represent and compare categorical data. They are ideal for showcasing contrasts among distinct categories, ranking data, and displaying relationships between variables.

    Line Charts: Line charts display data points connected by line segments, showing trends over time. They are useful for analyzing trends, comparing multiple data series, and visualizing time-series data.

    Pie Charts: Pie charts represent data as slices of a circle, showing numerical proportions. They are best for displaying parts of a whole and are effective with a small number of categories.

    Scatter Plots: Scatter plots use dots to represent data points, showing relationships between two numerical variables. They help identify trends, outliers, and subgroup variations.

    Histograms: Histograms display the distribution of numerical data by dividing it into intervals and showing the frequency of data points as bars. They are valuable for visualizing data distributions, detecting outliers, and assessing data quality.

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