Convert List to Pandas Dataframe Column

Question

I need to Convert my list into a one column pandas dataframe

Current List (len=3):

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


        

Answer 1

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

Answer 2

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

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

to get this:

  col1
0   1
1   2
2   3

Answer 3

You can directly call the

pd.DataFrame()

method and pass your list as parameter.

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

Answer 4

For Converting a List into Pandas Core Data Frame, we need to use DataFrame Method from pandas Package.

There are Different Ways to Perform the Above Operation.

import pandas as pd

1. pd.DataFrame({'Column_Name':Column_Data})

• Column_Name : String
• Column_Data : List Form

2. Data = pd.DataFrame(Column_Data)

   Data.columns = ['Column_Name']

So, for the above mentioned issue, the code snippet is

import pandas as pd

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

Data = pd.DataFrame({'Text': Content})

Answer 5

Example:

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

code block:

import pandas as pd
df = pd.DataFrame(lst)

Output:

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

It is not recommended to remove the column names of the panda dataframe. but if you still want your data frame without header(as per the format you posted in the question) you can do this:

df = pd.DataFrame(lst)    
df.columns = ['']

Output will be like this:

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

or

df = pd.DataFrame(lst).to_string(header=False)

But the output will be a list instead of a dataframe:

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

Hope this helps!!