How can I convert list of string to pandas DataFrame in Python

Given the information you have provided, I have written a few lines of basic Python code.

# Import needed dependencies
import pandas as pd

Below is your data as shown above. I kept it in its original format, but added ‘%’ in the last column value for consistency sake.

mylist = [
'n      Au[%]     Ag[%]     Cu[%]     Zn[%]     Ni[%]     Pd[%]     Fe[%]     Cd[%]     mq[%]', 
'1   71.085    4.6578    22.468    1.6971    0.0292    0.0000    0.0627    0.0000    1.1019', 
'2   71.444    4.0611    22.946    1.4333    0.0400    0.0000    0.0763    0.0000    1.1298', 
'3   71.845    4.2909    22.308    1.4234    0.0293    0.0000    0.1031    0.0000    1.0750', 
'4   71.842    4.2794    22.290    1.4686    0.0339    0.0000    0.0856    0.0000    1.1334'
]

Extract the first list element as it contains the values that will be the column values.

# Extract the column values from the first row
col_values = mylist[0]
col_values = col_values.split()
del col_values[0]

Take each list element and brake it into it string components as well as delete the first element.

# Loop through each row of the file.

a_list = []

for row in mylist[1:]:
    
    row_values = row
    row_values = row_values.split()
    
    del row_values[0]
    a_list.append(row_values)

Collect all column values into a primary list called main_list.

# Count variable
count = 0
main_list = []

for col in col_values:

    temp_list = []
    for _list in a_list:
        temp_list.append(_list[count])
    
    main_list.append(temp_list)

    count += 1

Now let’s create a dictionary and use it to make a dataframe.

my_dct = {}

# Create custom dictionary based on dim's of main_list

for iteration in range(len(main_list)):
    my_dct.update({col_values[iteration]:main_list[iteration]})

my_df = pd.DataFrame(dct)

A quick screen capture of the above code run within a Kaggle notebook

Hopefully, you find this useful.