Select random rows

Writing Efficient Code with pandas

Leonidas Souliotis

PhD Candidate

Sampling random rows using pandas

start_time = time.time()
poker.sample(100, axis=0)
print("Time using sample: {} sec".format(time.time() - start_time))

Time using sample: 0.000750064849854 sec

Sampling random rows using numpy

start_time = time.time()
poker.iloc[np.random.randint(low=0, high=poker.shape[0], size=100)]
print("Time using .iloc[]: {} sec".format(time.time() - start_time))

Time using .iloc[]: 0.00103211402893 sec

Difference in speed: 37.6033057849%

Sampling random columns

start_time = time.time()
poker.sample(3, axis=1)
print("Time using .sample(): {} sec".format(time.time() - start_time))

Time using .sample(): 0.000683069229126 sec

N = poker.shape[1]
start_time = time.time()
poker.iloc[:,np.random.randint(low=0, high=N, size=3)]
print("Time using .iloc[]: {} sec".format(time.time() - start_time))

ime using .iloc[]: 0.0010929107666 sec

Difference in speed: 59.9999999998%

Let's do it!

Writing Efficient Code with pandas