I want to generate a conditional list of lists. The number of embedded lists is determined by the number of unique conditions, and each embedded list contains values from a given condition.
I can generate this list of lists using a for-loop. See the code below. However, I am looking for a faster and more Pythonic (i.e, no for-loop) approach.
import pandas as pd
from random import randint
example_conditions = ["A","A","B","B","B","C","D","D","D","D"]
example_values = [randint(-100,100) for _ in example_conditions ]
df = pd.DataFrame({
"conditions":example_conditions,
"values": example_values
})
lol = []
for condition in df["conditions"].unique():
sublist = df.loc[df["conditions"]==condition]["values"].values.tolist()
lol.append(sublist)
Thanks!
CodePudding user response:
Try:
x = df.groupby("conditions")["values"].agg(list).to_list()
print(x)
Prints:
[[-1, 78], [33, 74, -79], [59], [-32, -2, 52, -66]]
Input dataframe:
conditions values
0 A -1
1 A 78
2 B 33
3 B 74
4 B -79
5 C 59
6 D -32
7 D -2
8 D 52
9 D -66