Python pandas how can i create incrementing multiple variables using iteration

Question

I have dataframe, called df

Category    block   array_size  num_node    num_task    time
 DATA         2     100             1          1        0.104
 DATA         2     100             1          2        0.348
 DATA         2     100             1          1        2.837 
 DATA         2     1000            1          1        29.188
 DATA         2     1000            1          1       284.087

With this dataframe, I want to find out mean value of each configuration.
So the variables I want to have are(df_foo_{#block}_{#array_size}_{#num_task}),

df_foo_2_100_1 = df.loc[
    (df["num_task"] == 1) & 
    (df["block"] == 2) & 
    (df["array_size"] == 100)]["time"].mean()
df_foo_2_1000_1 = df.loc[
        (df["num_task"] == 1) & 
        (df["block"] == 2) & 
        (df["array_size"] == 1000)]["time"].mean()

How can I automatically create these variables by using the loop?

Thanks!

BENY · Accepted Answer · 2018-09-12 01:52:58Z

2

You can do groupby

df.loc[(df["num_task"] == 1) & (df["block"] == 2)].groupby('array_size').time.mean()
Out[206]: 
array_size
100       1.4705
1000    156.6375
Name: time, dtype: float64

Seems like you need

df.groupby(['num_task','block','array_size']).time.mean()
Out[208]: 
num_task  block  array_size
1         2      100             1.4705
                 1000          156.6375
2         2      100             0.3480
Name: time, dtype: float64

edited Sep 12, 2018 at 1:52

answered Sep 12, 2018 at 1:44

BENY

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1 Comment

jayko03 Over a year ago

Then, I have to create all different variables first, then assign the values which generated by groupby ?

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