Reputation: 31
I have the following panda dataframe:
df = pd.DataFrame({'trial_time': ['0', '0',
'1', '1'],
'Max Speed': [1., 2, 3, 4]})
I want to create a dataframe that would for each unique value in trial_time bin/grab the corresponding values in an array. So 0 -> [1,2] 1 -> [3,4]
I read through pandas groupby documentation, but I'm still a bit stuck...
Upvotes: 1
Views: 894
Reputation: 14459
You could use the following code:
s = df.groupby('trial_time')['Max Speed'].apply(lambda x: list(x))
print(s)
trial_time
0 [1.0, 2.0]
1 [3.0, 4.0]
Name: Max Speed, dtype: object
So, this will return a pd.Series
with the unique values from trial_time
as the index, and the corresponding lists as data.
Upvotes: 1