在熊猫的元组列表中选择行

Question

I have a list of tuples as below in python:

   Index        Value
     0         (1,2,3)
     1         (2,5,4)
     2         (3,3,3)

How can I select rows from this in which the second value is less than or equal 2?

EDIT:

Basically, the data is in the form of [(1,2,3), (2,5,4), (3,3,3)....]

Answer 1

You could slice the tuple by using apply :

df[df['Value'].apply(lambda x: x[1] <= 2)]

---

Seems, it was a list of tuples and not a DF :

To return a list back:

data = [item for item in [(1,2,3), (2,5,4), (3,3,3)] if item[1] <= 2]
# [(1, 2, 3)]

To return a series instead:

pd.Series(data)
#0    (1, 2, 3)
#dtype: object

Answer 2

df[df["Value"].str[1] <= 2]

您可以阅读以获取更多详细信息-http://pandas.pydata.org/pandas-docs/stable/text.html#indexing-with-str

Answer 3

just to put this out there. you should read mcve . your question was/is confusing because it looks as though you've got 2 good answers and your not satisfied. then you edited your question to be clearer, but just barely.

ok, now that i've got my editorial out of the way.

---

setup
this is what i'm assuming i'm working with

# list of tuples
lot = [(1, 2, 3), (2, 5, 4), (3, 3, 3)]

desired output
i think. btw, nothing to do with pandas at all

[(a, b, c) for a, b, c in lot if b <= 2]

[(1, 2, 3)]

with pandas
however, since you did tag this pandas

s = pd.Series(lot)

@TrigonaMinima's answer, give them credit if this works for you.

s[s.str[1].le(2)]

0    (1, 2, 3)
dtype: object