James wrote:
Hi,
Thanks for all your help so far!
Right i think it would be easier to just show you the chart i have so far;
-------------------------- import numpy as np import matplotlib.pyplot as plt
plt.plot([4,8,12,16,20,24], [0.008,0.016,0.021,0.038,0.062,0.116], 'bo')
plt.xlabel("F (Number of washers)") plt.ylabel("v^2/r ms-2") plt.title("Circular Motion") plt.axis([2,26,0,0.120])
plt.show()
------------------------
Very basic i know, all i wish to do is add a line of best fit based on that data, in the examples there seems to be far more variables, do i need to split my data up etc?
Here is how I would do it: import numpy as np import matplotlib.pyplot as plt x = np.array([4,8,12,16,20,24]) y = np.array([0.008,0.016,0.021,0.038,0.062,0.116]) m = np.polyfit(x, y, 1) yfit = np.polyval(m, x) plt.plot(x, y, 'bo', x, yfit, 'k') plt.xlabel("F (Number of washers)") plt.ylabel("v2/r ms-2") plt.title("Circular Motion") plt.axis([2,26,0,0.120]) plt.text(5, 0.06, "Slope=%f" % m[0]) plt.text(5, 0.05, "Offset=%f" % m[1]) plt.show()