Pandas - Modify string values in each cell

Question

I have a pandas dataframe and I need to modify all values in a given string column. Each column contains string values of the same length. The user provides the index they want to be replaced for each value

for example: [1:3] and the replacement value "AAA".
This would replace the string from values 1 to 3 with the value AAA.

How can I use the applymap(), map() or apply() function to get this done?

SOLUTION: Here is the final solution I went off of using the answer marked below:

import pandas as pd

df = pd.DataFrame({'A':['ffgghh','ffrtss','ffrtds'],
                     #'B':['ffrtss','ssgghh','d'],
                     'C':['qqttss',' 44','f']})
print df
old = ['g', 'r', 'z']
new = ['y', 'b', 'c']
vals = dict(zip(old, new))

pos = 2
for old, new in vals.items():
    df.ix[df['A'].str[pos] == old, 'A'] = df['A'].str.slice_replace(pos,pos + len(new),new)
print df

root · Accepted Answer · 2016-07-25 16:44:28Z

15

Use str.slice_replace:

df['B'] = df['B'].str.slice_replace(1, 3, 'AAA')

Sample Input:

   A         B
0  w   abcdefg
1  x   bbbbbbb
2  y   ccccccc
3  z  zzzzzzzz

Sample Output:

   A          B
0  w   aAAAdefg
1  x   bAAAbbbb
2  y   cAAAcccc
3  z  zAAAzzzzz

answered Jul 25, 2016 at 16:44

root

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3 Comments

code base 5000 Over a year ago

@root - great answer, is it possible to add a condition to this as well, so say if position 1 is "A" replace with "B"?

root Over a year ago

Do you just have one condition, like an if-else statement, or multiple conditions, like an if-elif-else statement?

code base 5000 Over a year ago

@root multiple: example let's say the value is 'abcdef'. I need to replace position 3 in the string if values are ['a','b','c'] to match ['d','e','f'] where index 0 of list 1 matched the replace value in list 2.

MaxU - stand with Ukraine · Accepted Answer · 2016-07-25 16:37:16Z

3

IMO the most straightforward solution:

In [7]: df
Out[7]:
        col
0   abcdefg
1   bbbbbbb
2   ccccccc
3  zzzzzzzz

In [9]: df.col = df.col.str[:1] + 'AAA' + df.col.str[4:]

In [10]: df
Out[10]:
        col
0   aAAAefg
1   bAAAbbb
2   cAAAccc
3  zAAAzzzz

answered Jul 25, 2016 at 16:37

MaxU - stand with Ukraine

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