Density Plots in Python | Jupyter Notebook | Python Data Science for beginners | Data visualisation

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Density plots, also known as kernel density estimation plots, are a way to visualize the distribution of a continuous variable. They are similar to histograms, but instead of showing the frequency of data points in certain bins, they show the estimated probability density of the data. In other words, a density plot gives an idea of how likely it is for a certain value to occur within the data.

To create a density plot in Python, one can use the library Matplotlib. Matplotlib is a widely used library for data visualization in Python and has many built-in functions for creating various types of plots, including density plots.

To create a density plot using Matplotlib, one needs to first import the library and then use the function density() or kdeplot(). The function takes in the data that needs to be plotted and creates the density plot. One can also customize the appearance of the plot by passing in various parameters such as color, line width, and kernel type.

It’s also possible to overlay multiple density plots on the same graph to compare the distribution of different variables.

A density plot is a smooth version of a histogram and can be used to show the underlying probability density function of the data. It’s useful for understanding how the data is distributed and can help identify any outliers or unusual observations.

In summary, Density plots are a way to visualize the distribution of a continuous variable. They are similar to histograms, but instead of showing the frequency of data points in certain bins, they show the estimated probability density of the data. To create a density plot in Python, one can use the library Matplotlib which has many built-in functions for creating various types of plots, including density plots. This can be useful for understanding how the data is distributed and can help identify any outliers or unusual observations.

 

In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in Python programming: Density Plots in Python.

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Density Plots in Python:



 

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