Convert List to Pandas Dataframe Column

If your list looks like [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

Example:

['Thank You',
 'It's fine no problem',
 'Are you sure?']

Code block:

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

Output:

    0
0    Thank You
1    It's fine no problem
2    Are you sure?

It is not recommended to remove the column names of the Pandas 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    Thank You
1    It's 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             Thank You
1  It's fine no problem
2         Are you sure?

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

For converting a list into Pandas core data frame, we need to use DataFrame method from the pandas package.

There are different ways to perform the above operation (assuming Pandas is imported as pd)

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

• Column_Name : String
• Column_Data : List form

2.  Data = pandas.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})

You can also assign() a list to an existing dataframe. This is especially useful if you’re chaining multiple methods and you need to assign a column that you need to use later in the chain.

df = pd.DataFrame()
df1 = df.assign(col=['Thanks You', 'Its fine no problem', 'Are you sure'])

list = ['Thanks You', 'Its fine no problem', 'Are you sure']
df = pd.DataFrame(list)

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

Column name:

df.columns = ['col name']