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pythonlistpandasdataframe
Inherited Geek
Inherited Geek

Reputation: 2393

Convert List to Pandas Dataframe Column

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']

Required Pandas DF (shape =3,):

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

N.B. The numbers represent index in the required Pandas DF above.

Upvotes: 170

Views: 578121

Answers (7)

Grant Shannon
Grant Shannon

Reputation: 5055

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

Upvotes: 41

Milan
Milan

Reputation: 71

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

Output:

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

Column name:

df.columns = ['col name']

Upvotes: 3

Sadiq Raza
Sadiq Raza

Reputation: 354

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

Upvotes: 11

Prafulla Diwesh
Prafulla Diwesh

Reputation: 41

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?

Upvotes: 4

Kranthi
Kranthi

Reputation: 490

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
  1.  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})

Upvotes: 3

cottontail
cottontail

Reputation: 23111

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'])

res

Upvotes: 1

jezrael
jezrael

Reputation: 862611

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

Upvotes: 279

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