You can use scatter for this, but that requires having numerical values for your key1, and you won’t have a legend, as you noticed. It’s better to just use plot for discrete categories like this. For example: import matplotlib.pyplot as plt import numpy as np import pandas as pd np.random.seed(1974) # Generate Data num = … Read more
From the documentation for scatter: Optional kwargs control the Collection properties; in particular: edgecolors: The string ‘none’ to plot faces with no outlines facecolors: The string ‘none’ to plot unfilled outlines Try the following: import matplotlib.pyplot as plt import numpy as np x = np.random.randn(60) y = np.random.randn(60) plt.scatter(x, y, s=80, facecolors=”none”, edgecolors=”r”) plt.show() Note: … Read more
I think all that you’re missing is a call to caxis to specify the minimum and maximum values to map the color range to: caxis([18 23]); Note that the following line… cb.Limits = [18 23]; … only changes the tick limits displayed on the colorbar, but doesn’t change anything about how the data is mapped … Read more
This complete example creates a suitable database table in memory, queries it into a JDBCXYDataset and displays the dataset in a scatter plot. Note how the first column becomes the domain, while successive columns become individual series. import java.awt.EventQueue; import java.sql.Connection; import java.sql.Date; import java.sql.DriverManager; import java.sql.PreparedStatement; import java.sql.SQLException; import java.sql.Statement; import java.util.Calendar; import java.util.Random; … Read more