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I'm cleaning a dataset and need to take the part of the string between the underscores (_). Column A is what I am starting with.
A
foo_bar_foo
bar_foo_bar
bar
foo_bar_foo
I need to copy over the characters in between the underscores and copy them into a new column. Column B is the anticipated results.
A B
foo_bar_foo bar
bar_foo_bar foo
bar null
foo_bar_foo bar
Any advice is appreciated.
389
split() Pandas provide a method to split string around a passed separator/delimiter. After that, the string can be stored as a list in a series or it can also be used to create multiple column data frames from a single separated string.
You can use the following basic syntax to split a string column in a pandas DataFrame into multiple columns: #split column A into two columns: column A and column B df[[' A ', ' B ']] = df[' A ']. str. split (', ', 1, expand= True) The following examples show how to use this syntax in practice. Example 1: Split Column by Comma
Copy & Insert Row / Column Instead you can insert the copied row or column and shift the existing rows or columns to make room. This will copy row 1 and insert it into row 5, shifting the existing rows down: Range ("1:1").Copy Range ("5:5").Insert
Using the inbuilt function strcpy () from string.h header file to copy one string to the other. strcpy () accepts a pointer to the destination array and source array as a parameter and after copying it returns a pointer to the destination string.
When pasting rows and columns you have two options: You can paste over the existing row (or column) or you can insert a new row (or column). Let’s look at the difference… Copy & Paste Over Existing Row / Column This will copy row 1 and paste it into the existing row 5:
Use str.split and .str[index]
df['B']=df.A.str.split('_').str[1]
A B
0 foo_bar_foo bar
1 bar_foo_bar foo
2 bar NaN
3 foo_bar_foo bar
Use extract:
df['B'] = df['A'].str.extract('_(\w+)_')
print(df)
Output
A B
0 foo_bar_foo bar
1 bar_foo_bar foo
2 bar NaN
3 foo_bar_foo bar
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