Lussen met de functie .iterrows()

Efficiënte code schrijven met pandas

Leonidas Souliotis

PhD Candidate

De poker-dataset

	S1	R1	S2	R2	S3	R3	S4	R4	S5	R5
1	1	10	3	11	3	13	4	4	2	1
2	2	11	2	13	2	10	2	12	2	1
3	3	12	3	11	3	13	3	10	3	1

Harten
Ruiten
Klaveren
Schoppen

Generators in Python

def city_name_generator():
    yield('New York')
    yield('London')
    yield('Tokyo')
    yield('Sao Paolo')

city_names = city_name_generator()

next(city_names)
'New York'
next(city_names)
'London'
next(city_names)
'Tokyo'
next(city_names)
'Sao Paolo'

next(city_names)

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration

Lussen met de functie .iterrows()

gen = poker.iterrows()
first_element = next(gen)

first_element[0]
0

first_element[1]
S1     2
R1    11
S2     2
R2    13
S3     2
R3    10
S4     2
R4    12
S5     2
R5     1
Name: 1, dtype: int64

De functie .iterrows() gebruiken

start_time = time.time()
for index, values in range(poker.shape[0]):
    next
print("Time using range(): {} sec".format(time.time() - start_time))

Results using range(): 0.006870031 sec

data_generator = poker.iterrows()

start_time = time.time()
for index, values in data_generator:
    next
print("Time using .iterrows(): {} sec".format(time.time() - start_time))

Time using .iterrows(): 1.55003094673 sec

Aan de slag!

Efficiënte code schrijven met pandas