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Instead of lists, you’re now using NumPy arrays. You can notice a few changes from the first example. scatter ( x = price, y = sales_per_day, s = profit_margin * 10 ) plt. Import matplotlib.pyplot as plt import numpy as np price = np. In the next section, you’ll start exploring more advanced uses of plt.scatter().
![scatter plot matplotlib even odd points scatter plot matplotlib even odd points](https://vrzkj25a871bpq7t1ugcgmn9-wpengine.netdna-ssl.com/wp-content/uploads/2019/01/matplotlib-scatter-plot-size-120-points-1.png)
This alias is generally used by convention to shorten the module and submodule names. In this Python script, you import the pyplot submodule from Matplotlib using the alias plt. Import matplotlib.pyplot as plt price = sales_per_day = plt. You don’t need to be familiar with Matplotlib to follow this tutorial, but if you’d like to learn more about the module, then check out Python Plotting With Matplotlib (Guide). To get the most out of this tutorial, you should be familiar with the fundamentals of Python programming and the basics of NumPy and its ndarray object.
SCATTER PLOT MATPLOTLIB EVEN ODD POINTS HOW TO
Matplotlib provides a very versatile tool called plt.scatter() that allows you to create both basic and more complex scatter plots.īelow, you’ll walk through several examples that will show you how to use the function effectively. One of the most popular modules is Matplotlib and its submodule pyplot, often referred to using the alias plt. Python has several third-party modules you can use for data visualization.
![scatter plot matplotlib even odd points scatter plot matplotlib even odd points](https://storage.googleapis.com/coderzcolumn/static/tutorials/data_science/connection-map-plotly-4.jpg)
Watch it together with the written tutorial to deepen your understanding: Using plt.scatter() to Visualize Data in PythonĪn important part of working with data is being able to visualize it. Watch Now This tutorial has a related video course created by the Real Python team.