Usar:

 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

Gracias DYZ :

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

si su lista se ve así: [1,2,3] puede hacer:

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

para conseguir esto:

 col1 col2 col3 0 1 2 3

alternativamente, puede crear una columna de la siguiente manera:

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

para conseguir esto:

 col1 0 1 1 2 2 3

Puede llamar directamente al método pd.DataFrame() y pasar su lista como parámetro.

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

Producción:

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

Y si tiene varias listas y desea crear un marco de datos a partir de ellas. Puedes hacerlo de la siguiente manera:

 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()

Producción:

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