First, initialize a 30-by-3 array for the estimates as follows:

estimates = np.zeros((len(c), 3))

Loop through the values and generate a new dataset by setting one value to NaN at each iteration of the loop. For each new set of values, compute the estimates:

for i in xrange(len(c)):
   a = c.copy()
   a[i] = np.nan

   estimates[i,] = [np.nanmean(a), np.nanvar(a), np.nanstd(a)]

Print the variance for each estimate (you can also print the mean or standard deviation if you prefer):

print("Estimates variance", estimates.var(axis=0))

The following is printed on the screen:

Estimates variance [ 0.05960347  3.63062943  0.01868965]