Generate combinations of groups in pandas Series or DataFrame

Question

I have a pandas DataFrame set up like this:

 Type     time
 A        0
 A        1
 A        2
 B        0
 B        1
 B        2

I need to generate a list (or a Series) structured as follows:

["A.1-A.0", "A.2-A.0", "B.1"-"B.0", "B.2"-"B.0"]

Would groupby or similar functions would be able to generate such a list (or Series)?

HYRY · Accepted Answer · 2013-03-19 10:41:43Z

2

import pandas as pd
from StringIO import StringIO

data =  StringIO("""Type     time
A        0
A        1
A        2
B        10
B        11
B        12""")
df = pd.read_csv(data, delim_whitespace=True, dtype="O")

def set_first(x):
    x["ptime"] = x.time.values[0]
    x = x[1:]
    r = x.Type + "." + x.time + "-" + x.Type + "." + x.ptime
    return r

print df.groupby(df.Type, group_keys=False).apply(set_first)

output:

1      A.1-A.0
2      A.2-A.0
4    B.11-B.10
5    B.12-B.10

answered Mar 19, 2013 at 10:41

HYRY

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1 Comment

Einar Over a year ago

Thanks, ended up implementing something very similar to this.

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