I have a nested list as shown below:
A = [('a', 'b', 'c'),
('d', 'e', 'f'),
('g', 'h', 'i')]
and I am trying to print the first element of each list using the code:
A = [('a', 'b', 'c'), ('d', 'e', 'f'), ('g', 'h', 'i')]
print A[:][0]
But I get the following output:
('a', 'b', 'c')
Required output:
('a', 'd', 'g')
How to get this output in Python?
A[:] just creates a copy of the whole list, after which you get element 0 of that copy.
You need to use a list comprehension here:
[tup[0] for tup in A]
to get a list, or use tuple() with a generator expression to get a tuple:
tuple(tup[0] for tup in A)
Demo:
>>> A = [('a', 'b', 'c'), ('d', 'e', 'f'), ('g', 'h', 'i')]
>>> [tup[0] for tup in A]
['a', 'd', 'g']
>>> tuple(tup[0] for tup in A)
('a', 'd', 'g')
You can transpose a list of lists/tuples with zip(*list_of_lists) then select the items you want.
>>> a
[('a', 'b', 'c'), ('d', 'e', 'f'), ('g', 'h', 'i')]
>>> b = zip(*a)
>>> b
[('a', 'd', 'g'), ('b', 'e', 'h'), ('c', 'f', 'i')]
>>> b[0]
('a', 'd', 'g')
>>>
>>> c = zip(*a)[0]
>>> c
('a', 'd', 'g')
>>>
You can also do it this way:
>>> A = [('a', 'b', 'c'), ('d', 'e', 'f'), ('g', 'h', 'i')]
>>> map(lambda t:t[0], A)
['a', 'd', 'g']
>>> tuple(map(lambda t:t[0],A))
('a', 'd', 'g')
Python lists don't work very well as multi-dimensional arrays.
If you're willing to add an extra dependency(e.g. if you're going to do a lot of array manipulation), numpy allows you to use the almost the exact syntax you're looking for
import numpy as np
A = np.array([('a', 'b', 'c'),
('d', 'e', 'f'),
('g', 'h', 'i')])
This outputs the row as an np.array(which can be accessed like a list):
>>> A[:,0]
array(['a', 'd', 'g'])
To get the first row as a tuple:
>>> tuple(A[:,0])
('a', 'd', 'g')
You can also get the behavior you want using pandas as follows:
In [1]: import pandas as pd
In [2]: A = [('a', 'b', 'c'),
('d', 'e', 'f'),
('g', 'h', 'i')]
In [3]: df = pd.DataFrame(A)
In [4]: df[:][0]
Out[4]:
0 a
1 d
2 g
Name: 0, dtype: object
In [5]: df[:][0].values
Out[5]: array(['a', 'd', 'g'], dtype=object)
