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converting a list to datafame pandas

Creating a list in a loop, my final list looks like below:

L [col1, col2, col3, col4
0 N 225.0 12.0 03.0 B ,
col1, col2, col3, col4
0 W 223.0 12.0 01.0 M ,
col1, col2, col3, col4
0 X 203.0 11.0 04.0 P ]


Im trying to convert this to a pandas DataFrame?

Each row looks like a proper dataframe in itself:

L[0]
col1 col2 col3 col4
N 225.0 12.0 03.0 B


2 Answers
2

I believe need create 2d numpy array with DataFrame contructor:

DataFrame

L = ['col1', 'col2', 'col3', 'col4',
'N 225.0', '12.0', '03.0', 'B' ,
'col1', 'col2', 'col3', 'col4',
'W 223.0', '12.0', '01.0', 'M' ,
'col1', 'col2', 'col3', 'col4',
'X 203.0', '11.0', '04.0', 'P' ]

a = np.array(L).reshape(-1, 8)[:, -4:]
print (a)
[['N 225.0' '12.0' '03.0' 'B']
['W 223.0' '12.0' '01.0' 'M']
['X 203.0' '11.0' '04.0' 'P']]

df = pd.DataFrame(a, columns = L[:4])
print (df)
col1 col2 col3 col4
0 N 225.0 12.0 03.0 B
1 W 223.0 12.0 01.0 M
2 X 203.0 11.0 04.0 P


Explanation:

First convert list to 1d numpy array:

print (np.array(L))
['col1' 'col2' 'col3' 'col4' 'N 225.0' '12.0' '03.0' 'B' 'col1' 'col2'
'col3' 'col4' 'W 223.0' '12.0' '01.0' 'M' 'col1' 'col2' 'col3' 'col4'
'X 203.0' '11.0' '04.0' 'P']


then reshape to Nx8 nd array:

print (np.array(L).reshape(-1, 8))
[['col1' 'col2' 'col3' 'col4' 'N 225.0' '12.0' '03.0' 'B']
['col1' 'col2' 'col3' 'col4' 'W 223.0' '12.0' '01.0' 'M']
['col1' 'col2' 'col3' 'col4' 'X 203.0' '11.0' '04.0' 'P']]


And last select last 4 colums:

print (np.array(L).reshape(-1, 8)[:, -4:])
[['N 225.0' '12.0' '03.0' 'B']
['W 223.0' '12.0' '01.0' 'M']
['X 203.0' '11.0' '04.0' 'P']]


,

'

L

Try this

L = ['Thanks You', 'Its fine no problem', 'Are you sure']

#create new df
df = pd.DataFrame({'col':L})
print (df)


col1

col2

col3

col4

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