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Histograms, while useful, do have some limitations. They can sometimes be misleading if the bins are not chosen appropriately. The choice of bin size and starting point can significantly affect the resulting visualization, potentially obscuring important features of the data. Additionally, histograms can only represent the frequency of single variables and do not easily allow for the visualization of relationships between multiple variables. They also do not provide exact values for the data points, only a general distribution.
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Say you're a scientist, and you have a list of data that involves a specific gender and height. The first three histograms visualize the count of each height by gender, the distribution of the two genders, or the distribution of all the heights. But remember: these inputs can be customized to anything you want; say you run a warehouse, and you want to organize related parts by their respective sizes; delete the inputs in blue, and replace them with your specifications. Histograms work by separating data into groupings called bins. Here, we provide a simple filter to decide how to slice the data.
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