CODEWITHSUNDEEP
pythonpandasstringdataframeseries
Hassaballah El Kafrawi
Hassaballah El Kafrawi

Reputation: 1

How to create a new Dataframe column from an existing string column using split() method?

I have a dataframe column with data like this:

| column_1 | 
| -------- | 
| 1:3      | 
| 1:4      |
| 1:6      |
| 5:6      |

I want to split this column into to two colums like this:

| column_1 | left_split     | right_split |
| -------- | -------------- | -------------- |
| 1:3      | 1              | 3              |
| 1:4      | 1              | 4              |
| 1:6      | 1              | 6              |
| 5:6      | 5              | 6              |

Now I have tried using this code:

df['left_split'] = df['column_1'].split(':')[0]
df['right_split'] = df['column_1'].split(':')[1]

and this code:

df['left_split'] = df['column_1'].lsplit(':')
df['right_split'] = df['column_1'].rsplit(':')

and also this:

df['left_split'] = df['column_1'].strip(':')[0]
df['right_split'] = df['column_1'].strip(':')[1]

However, these codes returns an attribute error "'Series' object has no attribute 'split'"

I am confused since when I type this:

df['column_1'].iloc[1].split(':')[0]

it works and displays the left sided number but when I remove the iloc (to apply it on all the column) and assign it to a new column, it does not work.

Would appreciate your help on this

Thanks,

Upvotes: 0

Views: 83

Answers (1)

Andreas
Andreas

Reputation: 9217

You can use the expand=True parameter in split, like this:

df[['left_split', 'right_split']] = df['column_1'].str.split(':', expand=True)

Full example:

import pandas as pd
df = pd.DataFrame( {'column_1': {1: '1:3', 2: '1:4', 3: '1:6', 4: '5:6'}})
df[['left_split', 'right_split']] = df['column_1'].str.split(':', expand=True)

print(df)
#   column_1 left_split right_split
# 1      1:3          1           3
# 2      1:4          1           4
# 3      1:6          1           6
# 4      5:6          5           6

Upvotes: 1

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