Use:

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

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

                   col
0           Thanks You
1  Its fine no problem
2         Are you sure

df = pd.DataFrame({'oldcol':[1,2,3]})

#add column to existing df 
df['col'] = L
print (df)
   oldcol                  col
0       1           Thanks You
1       2  Its fine no problem
2       3         Are you sure

Thank you DYZ:

#default column name 0
df = pd.DataFrame(L)
print (df)
                     0
0           Thanks You
1  Its fine no problem
2         Are you sure

if your list looks like this: [1,2,3] you can do:

import pandas as pd

lst = [1,2,3]
df = pd.DataFrame([lst])
df.columns =['col1','col2','col3']
df

to get this:

    col1    col2    col3
0   1       2       3

alternatively you can create a column as follows:

import numpy as np
import pandas as pd

df = pd.DataFrame(np.array([lst]).T)
df.columns =['col1']
df

to get this:

  col1
0   1
1   2
2   3

You can directly call the pd.DataFrame() method and pass your list as the parameter.

import pandas as pd
l = ['Thanks You','Its fine no problem','Are you sure']
pd.DataFrame(l)

Output:

                      0
0            Thanks You
1   Its fine no problem
2          Are you sure

And if you have multiple lists and you want to make a dataframe out of it. You can do it as following:

import pandas as pd
names =["A","B","C","D"]
salary =[50000,90000,41000,62000]
age = [24,24,23,25]
data = pd.DataFrame([names,salary,age]) #Each list would be added as a row
data = data.transpose() #To Transpose and make each rows as columns
data.columns=['Names','Salary','Age'] #Rename the columns
data.head()

Output:

    Names   Salary  Age
0       A    50000   24
1       B    90000   24
2       C    41000   23
3       D    62000   25