Tip! If you’re working in the Jupyter environment, be sure to include the %matplotlib inline Jupyter magic to display the histogram inline. This hist function takes a number of arguments, the key one being the bins argument, which specifies the number of equal-width bins in the range. To create a histogram in Python using Matplotlib, you can use the hist() function. Creating a Histogram in Python with Matplotlib It might make sense to split the data in 5-year increments. We can see from the data above that the data goes up to 43. We can then create histograms using Python on the age column, to visualize the distribution of that variable. Let’s begin by loading the required libraries and our dataset. The histogram can turn a frequency table of binned data into a helpful visualization: Loading our Dataset If you want to learn how to create your own bins for data, you can check out my tutorial on binning data with Pandas. The shape of the histogram displays the spread of a continuous sample of data. The taller the bar, the more data falls into that range. Creating a Histogram in Python with PandasĪ histogram is a chart that uses bars represent frequencies which helps visualize distributions of data.īars can represent unique values or groups of numbers that fall into ranges.Changing Matplotlib Histogram Appearance.Creating a Histogram in Python with Matplotlib.
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