pierre_loic :
Suppose we have this simple pandas.DataFrame:
import pandas as pd
df = pd.DataFrame(
columns=['quantity', 'value'],
data=[[1, 12.5], [3, 18.0]]
)
>>> print(df)
quantity value
0 1 12.5
1 3 18.0
I would like to create a new column, say modified_value, that applies a function N times to the value column, N being the quantity column.
Suppose that function is new_value = round(value/2, 1), the expected result would be:
quantity value modified_value
0 1 12.5 6.2 # applied 1 time
1 3 9.0 1.1 # applied 3 times, 9.0 -> 4.5 -> 2.2 -> 1.1
What would be an elegant/vectorized way to do so?
Quang Hoang :
You can write a custom repeat function, then use apply:
def repeat(func, x, n):
ret = x
for i in range(int(n)):
ret = func(ret)
return ret
def my_func(val): return round(val/2, 1)
df['new_col'] = df.apply(lambda x: repeat(my_func, x['value'], x['quantity']),
axis=1)
# or without apply
# df['new_col'] = [repeat(my_func, v, n) for v,n in zip(df['value'], df['quantity'])]
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