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As you can see in the picture, I want to convert the array to a list and finally to excel. But the problem I have is all the data on both sides have square brackets and quotations. what should I do to remove them? please help me to solve this problem, thank you!

To put it simply: My list is like [['a'], ['b'], ['c']] and I want to convert it to a,b,c

here is my code

def top_rank(result, md_adj, miRNAs, diseases):
row, col = result.shape
rows_list = []

for i in range(3):
    pidx = np.argsort(-result[:, i])
    sidx = np.argwhere(md_adj[:, i] == 1)
    indices = np.argwhere(np.isin(pidx, sidx))
    index = np.delete(pidx, indices)
    a = diseases[i]
    b = miRNAs[index]
    c = np.vstack([a,b]).tolist()
    rows_list.append(c)


df = pd.DataFrame(rows_list)
df = df.T
df.to_excel('test.xlsx')

CodePudding user response：

If you have nested lists [['a'], ['b'], ['c']] then you can use for-loop to make it flatten ['a', 'b', 'c']

data = [ ['a'], ['b'], ['c']]

flatten = [row[0] for row in data]

print(flatten)

Or you can also use fact that ["a"] ["b"] gives ["a", "b"] - so you can use sum() with [] as starting value

data = [['a'], ['b'], ['c']]

flatten = sum(data, [])

print(flatten)

And if you have numpy.array then you could simply use arr.flatten()

import numpy as np

data = [['a'], ['b'], ['c']]
arr = np.array(data)

flatten = arr.flatten()

print(flatten)

BUT ... images show that you have [['X', 'Y'], ['a'], ['b'], ['c']] and first element has two values - and this need different method to create flatten ['X Y', 'a', 'b', 'c']. It needs to use for-loop with join()

data = [['X', 'Y'], ['a'], ['b'], ['c']]

flatten = [' '.join(row) for row in data]

print(flatten)

The same using map()

data = [['X', 'Y'], ['a'], ['b'], ['c']]

flatten = list(map(",".join, data))

print(flatten)

And when you have flatten list then your code

rows_list = [flatten]

df = pd.DataFrame(rows_list)
df = df.T

print(df)

gives

     0
0  X Y
1    a
2    b
3    c

without [] and ''

BTW:

If you would creat dictionary rows_list[a] = b (after converting a to string and b to flatten list) then you wouldn't need to transpose df = df.T

import pandas as pd

a = [['X', 'Y']]
b = [['a'], ['b'], ['c']]

print('a:', a)
print('b:', b)
print('---')

a = " ".join(sum(a, []))
b = sum(b, [])

print('a:', a)
print('b:', b)
print('---')

rows = dict()
rows[a] = b

df = pd.DataFrame(rows)
print(df)

gives

a: [['X', 'Y']]
b: [['a'], ['b'], ['c']]
---
a: X Y
b: ['a', 'b', 'c']
---
  X Y
0   a
1   b
2   c