CODEWITHSUNDEEP
pythonpandas
Jacob2309
Jacob2309

Reputation: 91

How to split a column into 4 columns based on spaces in python?

I have seen similar questions, but it seems all would not work in Python 3.8. I have a dataframe like

index id
0   0001 01 12537.30 0
1   0001 01 1278.50 1
2   0001 03 53.10 0

where id column should be split into 4 columns, but they are in one column now. I need to split it based on space.

I have tried

df2 = df1['id'].apply(lambda x: pd.Series(x.split(' ')))

or

df1[["City", "State", "Country",'indicator']] = df1["id"].str.split(pat=" ", expand=True)

All told me that TypeError: 'function' object is not subscriptable. Does anyone have any idea? Thanks

Upvotes: 0

Views: 1401

Answers (2)

Fareed Khan
Fareed Khan

Reputation: 2923

Pretty late, but this is what you can do:

df['id'].str.extractall('(\w+)')[0].unstack()

Here is the link to the original answer (Link

Upvotes: 0

Heapify
Heapify

Reputation: 2901

Instead of going through the hassle of splitting the column, the easy path for you would be to create a new Dataframe with read_csv method where the sep argument as spaces or tab (whatever you have there) and skiprows argument as 1 and names=[co1, col2, col3,...].

Here is an example to further clarify the above point:

new_df = pd.read_csv(path_to_your_file, sep='\\t', skiprows=1, names=['id', 'col1', 'col2', 'col3']

Upvotes: 1

Related Questions