Scan the tables to make a digital copy of them
I will hope this helps :p
Answer:
Chech the explanation
Explanation:
<em>In [16]:</em>
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# Your answer to this question might be written on more than a line.
datascience_trials = make_array()
for i in np.arange(1000):
datascience_trials = np.append(datascience_trials, simulate_several_key_strikes(1))
datascience_proportion = np.count_nonzero(datascience_trials == 'datascience')/1000
datascience_proportion
<em>Out [16]:</em>
0.0
<em>In [17]:</em>
_ = ok.grade('q2_4')
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#Running tests
