Hello,
I'm trying to learn if there is a better or less tedious way of changing the
x-axis time scale interval size when plotting time series data using
MATPLOTLIB.
To account for all the different x-axis intervals that I may end up using, I
usually do the following imports:
from matplotlib.dates
Are you trying to make 9 scatter plots? In your for loop, if you are
trying to make a set of x values and a set of y values, then I think this
is wrong. Since you didn't provide import statements I don't know which
rand() function you are using. Assuming it is scipy.rand(), you will only
have on
Sorry looks like my smartphone's copy/paste removed carriage return in
certain places in the script :-(
On Jun 13, 2012 12:32 PM, "Chris Withers" wrote:
> Hi all,
>
> I have some time series of disk usage that I'd like to do a linear
> regression on an plot on a nice graph with Mb used on the y-a
Check out linregress from scipy.stats module. Not sure if it will handle
dates. Sample script below:
from scipy.stats import pearsonr from scipy.stats import linregress from
matplotlib import pyplot as plt import numpy as np
sat = np.array([595,520,715,405,680,490,565]) gpa =
np.array([3.4,3.2,
