How to extract a value from a cell containing an array in pandas Dataframe?

Question

Here is pandas data frame format of the data source

    cinema       kiwi    restaurant         sushi
0  [2, 2, 2]  [5, 5, 5]     [2, 2, 2]  [14, 14, 14]
1  [2, 2, 2]  [2, 2, 2]     [2, 2, 2]     [2, 2, 2]
2  [1, 1, 1]  [1, 1, 1]  [10, 10, 10]     [1, 1, 1]

I would like to transform it as follow by choosing only the first value of the array

    cinema       kiwi    restaurant         sushi
0  2             5       2                  14
1  2             2       2                  2
2  1             1       10                 1

Is there any function to do that ? I was thinking about using the "apply" method but I am not sure if it the best/most straightforward way.

Thank you by advance for your comments.

Possible duplicate of Python Pandas: selecting 1st element in array in all cells — niraj
– niraj, Commented Dec 20, 2017 at 1:07

juanpa.arrivillaga · Accepted Answer · 2017-12-20 00:15:25Z

3

The most straight-forward way is to use .applymap:

In [3]: df
Out[3]:
      cinema       kiwi    restaurant         sushi
0  [2, 2, 2]  [5, 5, 5]     [2, 2, 2]  [14, 14, 14]
1  [2, 2, 2]  [2, 2, 2]     [2, 2, 2]     [2, 2, 2]
2  [1, 1, 1]  [1, 1, 1]  [10, 10, 10]     [1, 1, 1]

In [4]: df.applymap(lambda x: x[0])
Out[4]:
   cinema  kiwi  restaurant  sushi
0       2     5           2     14
1       2     2           2      2
2       1     1          10      1

answered Dec 20, 2017 at 0:15

juanpa.arrivillaga

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2 Comments

fixeme Over a year ago

Thank you very much ! I had to tweak that a little as I have NaN values. So I am using the following : > df.applymap(lambda x: x[0] if not np.all(pd.isnull(x)) else 0)

cs95 Over a year ago

@fixme If you need to account for NaNs too, you might use df.apply(lambda x: x.str[0], axis=0) instead.

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