...
| Code Block |
|---|
def do_stuff_with_number(n):
print(n)
def catch_this():
the_list = (1, 2, 3, 4, 5)
for i in range(20):
try:
do_stuff_with_number(the_list[i])
except IndexError: # Raised when accessing a non-existing index of a list
do_stuff_with_number('out of bound - %d' % i)
catch_this()
|
Numpy
Convert arrays to Numpy arrays
| Code Block |
|---|
# Create 2 new lists height and weight
height = [1.87, 1.87, 1.82, 1.91, 1.90, 1.85]
weight = [81.65, 97.52, 95.25, 92.98, 86.18, 88.45]
# Import the numpy package as np
import numpy as np
# Create 2 numpy arrays from height and weight
np_height = np.array(height)
np_weight = np.array(weight)
print(type(np_height))
# Calculate bmi
bmi = np_weight / np_height ** 2
# Print the result
print(bmi)
# For a boolean response
print(bmi > 23)
# Print only those observations above 23
print(bmi[bmi > 23]) |
Result
| Code Block |
|---|
<class 'numpy.ndarray'>
[ 23.34925219 27.88755755 28.75558507 25.48723993 23.87257618
25.84368152]
[ True True True True True True]
[ 23.34925219 27.88755755 28.75558507 25.48723993 23.87257618
25.84368152] |
Convert all of the weights from kilograms to pounds based in NumPy
| Code Block |
|---|
weight_kg = [81.65, 97.52, 95.25, 92.98, 86.18, 88.45]
import numpy as np
# Create a numpy array np_weight_kg from weight_kg
np_weight_kg = np.array(weight_kg)
# Create np_weight_lbs from np_weight_kg
np_weight_lbs = np_weight_kg * 2.2
# Print out np_weight_lbs
print(np_weight_lbs) |
Result
| Code Block |
|---|
[ 179.63 214.544 209.55 204.556 189.596 194.59 ] |
Pandas DataFrame / CSV / Join / Merge
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