How to apply some operations on only specific items in the list in Python or pandas?

user_17355262 0
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I have two lists:

main = [1,2,3,4,5,6,7,8,20]
replace_items = [6,8,20]

I want this replace items to replace with replace_items*10 i.e [60, 80,200]

So the result main list would be:

main = [1,2,3,4,5,60,7,80,200]

My trial:

I am getting an error:

for t in replace_items:
    for o in main:
       
        main = o.replace(t, -(t-100000), regex=True)

        print(main)

following is the error I am getting:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-592-d3f3f6915a3f> in <module>
     14         main = o.replace(t, -(t-100000), regex=True)
---> 15         print(main)
     
            

TypeError: replace() takes no keyword arguments
python-2.7 python-3.x list python
4 Answers

You can use list comprehension:

main = [x * 10 if x in replace_items else x for x in main]

Output:

print(main)
[1, 2, 3, 4, 5, 60, 7, 80, 200]
user_133401430

As you initially had a pandas tag, you might be interested in a vectorial solution.

Here using numpy

import numpy as np

main = np.array([1,2,3,4,5,6,7,8,20])
replace_items = np.array([6,8,20])  # a list would work too

main[np.in1d(main, replace_items)] *= 10

output:

>>> main
array([  1,   2,   3,   4,   5,  60,   7,  80, 200])
user_163434640

You can do this

for (index,mainItems) in enumerate(main) : 
    if mainItems in replace_items : 
        main[index] *= 10

By using enumerate(main) you have access to both index and item

user_159831620

Using pandas you can do

import pandas as pd
main = pd.Series([1,2,3,4,5,6,7,8,20])
replace_items = [6,8,20]
main[main.isin(replace_items)] *= 10
print(main.values)

Output

[  1   2   3   4   5  60   7  80 200]

Explanation: use pandas.Series.isin to find elements which are one of replace_items, something *= 10 is concise way to write something = something * 10

user_107859750
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