These lists are then passed to the scatter() method, where the colour for each point is specified by setting c=colors. We supply a colour for each point in the colours list and the coordinates for each point in the x and y lists. In this example, we create a scatter plot with several colours. The cmap argument can map this to a colormap as a single colour, a series of colours, or a series of values. c parameter defines the marker's shade of colour. Syntax import matplotlib.pyplot as pltÄata that will be plotted on the x and y axes are denoted by the letters x and y. For instance, a scatter plot with blue markers would be produced if c='blue' or c=(0.0, 0.0, 1.0, 1.0). The scatter plot's markers will all have the same colour if the c parameter is passed a single-colour string or a tuple of RGBA values. Depending on how the user wishes to relate the colours to the data, it can take various forms. The colour of each marker in a scatter plot is specified by the c parameter of Matplotlib's scatter function. We can learn more about the connections between variables and spot any intriguing trends or patterns by examining the plot that results. Moreover, the user may add labels, captions, and legends to the plot to offer context and details about the data. Use the scatter function in Matplotlib and the c parameter to pass in the x and y data and a list of colours to produce a scatter plot. This way, we can use the plot to visually depict a third variable or category. By giving a list of colours that each plot point should belong to, the user may use Matplotlib to produce a scatter plot with various hues. Scatter plots and other types of data visualisation can be made using the well-known Python module Matplotlib. The graphic can aid in finding patterns, trends, and outliers in the data. A marker or symbol is placed on the plot at the coordinates corresponding to each data point's values for the two variables, representing that data point. A scatter plot is a data visualisation that displays the relationship between two variables.
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