![]() Most times, it’s necessary to add texts or labels to the axes of the graphs to help viewers understand what the plot is actually about. Markerfacecolor is used to change the color of the marker to highlight it more, and markeredgecolor is used to change the borders: plt.plot(x, marker='o', markersize=10, markeredgecolor='black', We can change the size of the markers using the argument markersize. Here’s how they can be viewed, along with a few examples: Like linestyle, there’s a long list of selections of linemarkers. Markers are used to highlight points on the graph. Linewidth is used to change the thickness of the plot: plt.plot(x,linestyle='dashdot',color='green',linewidth=5) Let’s try out a few linestyles and some other arguments: plt.plot(x,linestyle=':',color='red') Here’s a list of all the available options: import matplotlib Matplotlib offers a variety of linestyles that can be customized using the ls or linestyle argument in the plot(). Let’s plot a simple line graph using sample data. ![]() Customizing plots using Matplotlib Line styles png images of the plot directly into the IPython Notebook. The %matplotlib inline command is used to embed static. Or, by running this command in cmd: conda install -c conda-forge matplotlib Matplotlib can installed directly from Jupyter Notebook by running the command: !pip install matplotlib Image source: Matplotlib Data visualization using Matplotlib Installation and loading ![]() It offers a variety of plots like Line, Scatter, Bar, Histogram, Box, etc. It is the go-to Python library for graphs and visualizations. Matplotlib was created by John Hunter during his post-doctoral research in neurobiology and released in 2003.
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