Create Pandas DataFrame in Python using same list for each of the columns

Question

I am trying to add the same column when creating a new Pandas DataFrame in Python. I am trying to do something like the following:

I am trying to make all columns of the DataFrame above the same list. Is it possible to do this for a list of integers (or more generally, a list of strings/objects/etc.)?

I've tried using arrays, dicts, lists for column names. This part is something I can figure out, but figuring out a scalable way to just pass in one list is what I am trying to figure out.

column_names = array(['col0', 'col1', 'col2', 'col3'], dtype=object)
some_list = [int0, int1, int2]

df = pd.DataFrame(some_list, columns=column_names)

I would like to see something like:

  col0 col1 col2 col3

0 int0 int0 int0 int0
1 int1 int1 int1 int1
2 int2 int2 int2 int2

BENY · Accepted Answer · 2019-04-29 01:22:24Z

3

IIUC, consider not using list as a variable (or any other reserved keyword), since list is a built in function and you will override it.

l = [0, 1, 2]
df = pd.DataFrame(dict.fromkeys(column_names,l))
df
   col0  col1  col2  col3
0     0     0     0     0
1     1     1     1     1
2     2     2     2     2

Another method

pd.DataFrame([l]*len(column_names),index=column_names).T
   col0  col1  col2  col3
0     0     0     0     0
1     1     1     1     1
2     2     2     2     2

edited Apr 29, 2019 at 1:22

answered Apr 29, 2019 at 1:03

BENY

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7 Comments

qxzsilver Over a year ago

Yup I forgot to use a different variable name. Edited now.

qxzsilver Over a year ago

Thanks for the help! How does this compare to other methods? For example, are there other methods besides using dict.fromkeys(column_names, some_list) and how would it compare (in terms of memory, time, etc.)?

BENY Over a year ago

@qxzsilver I would say , they almost the same, since you need to get the input data as same size of columns you want to build

BENY Over a year ago

@qxzsilver if this help , would u like accept and upvote ?

qxzsilver Over a year ago

This helped a lot! However, the dict.fromkeys(col_names, some_list) had the unwanted side effect of re-arranging the column names by alphabetical order for the column names within the DataFrame. Is there another workaround besides dictionary, since dictionary seems to arrange by column_names within memory.

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