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The primary difference of plt.scatter from plt.plot is that it can be used to create scatter plots where the properties of each individual point (size, face color, edge color, etc.) can be individually controlled or mapped to data. Let's show this by creating a random scatter plot with points of many colors and sizes.

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4.2.1 Scatterplot. The simplest display of two quantitative variables is a scatterplot, with each variable represented on an axis. For example, using the Salaries dataset, we can plot experience (yrs.since.phd) vs. academic salary (salary) for college professors.

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When your dependent variable is categorical and has more than two categories E.g., Race: Black, Asian, White, Other; Ordinal logistic regression When your dependent variable is ordinal and has more than two categories E.g., Education: (1=Less than High School, 2=High School, 3=More than High School)

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To visualize a small data set containing multiple categorical (or qualitative) variables, you can create either a bar plot, a balloon plot or a mosaic plot. For a large multivariate categorical data, you need specialized statistical techniques dedicated to categorical data analysis, such as simple and multiple correspondence analysis .

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Each point represents the values of two variables. One variable is chosen in the horizontal axis and another in the vertical axis. The simple scatterplot is created using the plot() function. Syntax. The basic syntax for creating scatterplot in R is − plot(x, y, main, xlab, ylab, xlim, ylim, axes) Following is the description of the ...

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First, let us make simple scatter plot with Matpplotlib in Python. One of the ways to make a scatter plot using Matplotlib is to use scatter() function in Matplotlib.pyplot. Below, we make scatter plot by specifying x and y-axes variables from the Pandas dataframe. We also add x and y-axis labels to the scatter plot made with Matplotlib.

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When two variables with a positive correlation are plotted on the two axes of an X-Y scatter chart, the points form a rough line or curve upward from left to right. The plot() function can be used to quickly create X-Y scatter plots. The first parameter is the X-axis and the second parameter is the Y-axis.