Efficiently Zip multiple list in python/pandas

Question

I have below Lists

Number = [[1],[2],[3],[4],[6]]
L1 = ['A','B','C','D','E']
L2 = [100, 55, 315, 68, 23]
L3 = ['18%','105','56%','12%','4%']

I wanted to Zip all the lists and create a DataFrame. I used the below code and successfully able to do it.

for n, l1, l2, l3 in zip(Number,L1,L2, L3):
    n.insert(1,l1)
    n.insert(2,l2)
    n.insert(3,l3)

df = pd.DataFrame(Number, columns=['Number','Name', 'Value', 'Score'])
print(df)

+---+--------+------+-------+-------+
|   | Number | Name | Value | Score |
+---+--------+------+-------+-------+
| 0 |    1   |   A  |  100  |  18%  |
+---+--------+------+-------+-------+
| 1 |    2   |   B  |   55  |  105  |
+---+--------+------+-------+-------+
| 2 |    3   |   C  |  315  |  56%  |
+---+--------+------+-------+-------+
| 3 |    4   |   D  |   68  |  12%  |
+---+--------+------+-------+-------+
| 4 |    6   |   E  |   23  |   4%  |
+---+--------+------+-------+-------+

Since there is only 4 lists in this example. Easily we can type manually for n, l1, l2, l3 in zip(Number,L1,L2, L3): and type individual insert functions. Now my question is, what if there is many lists (say 15)? is there a pythonic way of doing this?

Does this answer your question? Python: create a pandas data frame from a list — David Erickson
– David Erickson, Commented Jul 31, 2020 at 17:06
No. I'm asking about efficient way of Zipping multiple files. the above is different. — Sunni
– Sunni, Commented Jul 31, 2020 at 17:08
where is the mention of anything about zipping multiple files in your question? — David Erickson
– David Erickson, Commented Jul 31, 2020 at 17:09
you can try pd.DataFrame(zip(np.concatenate(Number),L1,L2,L3)) — anky
– anky, Commented Jul 31, 2020 at 17:11

jsmart · Accepted Answer · 2020-07-31 17:14:09Z

0

Does this meet the requirement? Make a dictionary with the name of each list, and the list itself. Then pass the dictionary to the DataFrame constructor (in the print statement below).

data = {
    'Number': Number,
    'L1': L1,
    'L2': L2,
    'L3': L3
}
df = pd.DataFrame(data).rename(columns={'L1': 'Name', 
                                        'L2': 'Value', 
                                        'L3': 'Score'})
print(df)

   Number Name  Value Score
0       1    A    100   18%
1       2    B     55   105
2       3    C    315   56%
3       4    D     68   12%
4       6    E     23    4%

edited Jul 31, 2020 at 17:14

answered Jul 31, 2020 at 17:08

jsmart

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1 Comment

Sunni Over a year ago

this answer doesn't work. because, Number is a list of lists. first we have to flatten this list by [item for sublist in Number for item in sublist]. after doing this, we can use your code

Dharman · Accepted Answer · 2020-07-31 17:14:50Z

0

I would definitely find a more resumed format to write this query! Out of the top of my head, I thought about this:

test = [Number, L1, L2, L3]
for t in zip(*test):
    print(t)

# on the first loop iteration:
# t = ([1], 'A', 100, '18%')
#t[3] = ['18%']

As you'll find, your results will now be in a tuple (e.g. ([1], 'A', 100, '18%')). So, if you need to access each value, e.g. the value from Number, you can do t[0].

edited Jul 31, 2020 at 17:14

Dharman♦

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answered Jul 31, 2020 at 17:09

rmssoares

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1 Comment

Sunni Over a year ago

Number is a list of list

aggis · Accepted Answer · 2020-07-31 17:20:42Z

0

I am not sure why you have Number be a list of lists. But, this may be what you're looking for:

Number = [1,2,3,4,6]
L1 = ['A','B','C','D','E']
L2 = [100, 55, 315, 68, 23]
L3 = ['18%','105','56%','12%','4%']

pd.DataFrame(list(zip(Number, L1, L2, L3)), columns=['Number', 'Name', 'Value', 'Score'])

output:

   Number Name  Value Score
0       1    A    100   18%
1       2    B     55   105
2       3    C    315   56%
3       4    D     68   12%
4       6    E     23    4%

answered Jul 31, 2020 at 17:20

aggis

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2 Comments

Sunni Over a year ago

Number is a list of list

aggis Over a year ago

It seems like you want to flatten the list then

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