CoCalc Public Filestmp / 2014-12-15-052620.ipynbOpen in with one click!
Author: William A. Stein
In [6]:
1+1
2
In [32]:
a = 1230 + 1456 + 11 a
2697
In [7]:
#test plot([1,2,3,4,5,10,20,200,10,0, 100])
[<matplotlib.lines.Line2D at 0x7f5b722a7190>]
{"metadata":{},"output_type":"display_data","png":"iVBORw0KGgoAAAANSUhEUgAAAXgAAAEACAYAAAC57G0KAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSZIkSZIkSZIkSZIkSZIkSZJ0Qv8PFvap8Mz0mj8AAAAASUVORK5CYII=\n","text":["<matplotlib.figure.Figure at 0x7f5b72d5fcd0>"]}

απ\alpha^\pi

In [11]:
42+30
72
In [4]:
%load_ext rmagic
In [5]:
%R X=c(1,4,5,7,20); sd(X); mean(X)
array([ 7.4])
In [20]:
2+100
102
In [22]:
%%R c(1,2,3)
{"metadata":{},"output_type":"display_data","text":["[1] 1 2 3\n"]}
In [12]:
c(1,2,3)
--------------------------------------------------------------------------- NameError Traceback (most recent call last) <ipython-input-12-3786a8804255> in <module>() ----> 1 c(1,2,3) NameError: name 'c' is not defined
In [37]:
import time for i in range(10): time.sleep(10) print i
--------------------------------------------------------------------------- KeyboardInterrupt Traceback (most recent call last) <ipython-input-37-b77f6134bc18> in <module>() 1 import time 2 for i in range(10): ----> 3 time.sleep(10) 4 print i KeyboardInterrupt:
In [38]:
2+50
52
In [ ]:
2+3