Python: Convert two columns of dataframe into one interposed list [duplicate]

Question

How can I convert two columns in a dataframe into an interposed list?

ex: I want to do something like

df

             Open  Close
Date
2016-12-23  1      2
2016-12-27  3      4
2016-12-28  5      6
2016-12-29  0      -1

someFunction(df)

>>> [1, 2, 3, 4, 5, 6, 0, -1]

Closest I've found is list(zip(df.Open, df.Close) but that returns a bunch of tuples in the list like this: [(1, 2), (3, 4), (5, 6), (0, -1)]

Does this answer your question? Pythonic way to combine two lists in an alternating fashion? — Simon Crane
– Simon Crane, Commented Dec 25, 2019 at 23:21

oppressionslayer · Accepted Answer · 2019-12-25 23:22:29Z

5

Try this:

df.values.flatten()                                                                                                                                                                  
# array([ 1,  2,  3,  4,  5,  6,  0, -1])

answered Dec 25, 2019 at 23:22

oppressionslayer

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3 Comments

Michael Over a year ago

Ah, what if there are a bunch of other columns in between? Is there a more pythonic way than just grabbing the first 2 columns into its own DF or dropping the rest of the columns?

oppressionslayer Over a year ago

If you want, you can just pick the columns you want to flatten: df[['Open', 'Close']].values.flatten()

ansev Over a year ago

this is: df.stack().values

BENY · Accepted Answer · 2019-12-25 23:18:59Z

2

IIUC

df.values.ravel().tolist()#df.to_numpy().ravel().tolist()

[1, 2, 3, 4, 5, 6, 0, -1]

answered Dec 25, 2019 at 23:18

BENY

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1 Comment

BENY Over a year ago

may I know the reason downvote ?

ansev · Accepted Answer · 2019-12-25 23:30:06Z

2

How about:

df.stack().values
#array([ 1,  2,  3,  4,  5,  6,  0, -1])

answered Dec 25, 2019 at 23:30

ansev

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Comments

willeM_ Van Onsem · Accepted Answer · 2019-12-25 23:19:05Z

1

You can obtain the values, and reshape it to a 1d array:

>>> df[['Open', 'Close']].values.reshape(-1)
array([ 1,  2,  3,  4,  5,  6,  0, -1])

or convert that to a list:

>>> list(df[['Open', 'Close']].values.reshape(-1))
[1, 2, 3, 4, 5, 6, 0, -1]

answered Dec 25, 2019 at 23:19

willeM_ Van Onsem

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Comments

KenHBS · Accepted Answer · 2019-12-25 23:19:37Z

1

You could use a list comprehension in combination with df.values:

[y for x in df.values for y in x]
[1, 2, 3, 4, 5, 6, 0, -1]

x will be an array with the rows, and y will be the values in those rows

answered Dec 25, 2019 at 23:19

KenHBS

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