.replace codes will not replace column with new column in python

Question

I am trying to read a column in python, and create a new column using python.

import pandas as pd 
df = pd.read_csv (r'C:\Users\User\Documents\Research\seqadv.csv') 
print (df)

df = pd.DataFrame(data={'WT_RESIDUE':['']})
codes = {'ALA':'A', 'ARG':'R', 'ASN':'N', 'ASP':'D', 'CYS':'C', 'GLU':'E', 'GLN':'Q', 'GLY':'G', 'HIS':'H', 'ILE':'I', 'LEU':'L', 'LYS':'K', 'MET':'M', 'PHE':'F', 'PRO':'P', 'SER':'S', 'THR':'T', 'TRP':'W', 'TYR':'Y', 'VAL':'V'}
df['MUTATION_CODE'] = df['WT_RESIDUE'].replace(codes)
df.to_csv (r'C:\Users\User\Documents\Research\output.csv')

I tried this, but it will not create a new column no matter what I do.

example

Can you please explain what column you are reading and what column you want to derive from it. Providing sample input and output will help. Please provide text and not images. — Utsav
– Utsav, Commented Apr 27, 2021 at 3:28

paradocslover · Accepted Answer · 2021-04-27 03:37:09Z

0

It seems like you made a silly mistake

import pandas as pd 
df = pd.read_csv (r'C:\Users\User\Documents\Research\seqadv.csv') 
print (df)

df = pd.DataFrame(data={'WT_RESIDUE':['']}) # Why do you have this line?
codes = {'ALA':'A', 'ARG':'R', 'ASN':'N', 'ASP':'D', 'CYS':'C', 'GLU':'E', 'GLN':'Q', 'GLY':'G', 'HIS':'H', 'ILE':'I', 'LEU':'L', 'LYS':'K', 'MET':'M', 'PHE':'F', 'PRO':'P', 'SER':'S', 'THR':'T', 'TRP':'W', 'TYR':'Y', 'VAL':'V'}
df['MUTATION_CODE'] = df['WT_RESIDUE'].replace(codes)
df.to_csv (r'C:\Users\User\Documents\Research\output.csv')

Try removing the line with the comment. AFAIK, it is reinitializing your DataFrame and thus the WT_RESIDUE column becomes empty.

edited Apr 27, 2021 at 3:37

answered Apr 27, 2021 at 3:33

paradocslover

3,3543 gold badges25 silver badges49 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

Utsav · Accepted Answer · 2021-04-27 03:33:12Z

0

Considering sample from provided input.
We can use map function to map the keys of dict to existing column and persist corresponding values in new column.

df = pd.DataFrame({
    'WT_RESIDUE':['ALA', "REMARK", 'VAL', "LYS"]
})
codes = {'ALA':'A', 'ARG':'R', 'ASN':'N', 'ASP':'D', 'CYS':'C', 'GLU':'E', 'GLN':'Q', 'GLY':'G', 'HIS':'H', 'ILE':'I', 'LEU':'L', 'LYS':'K', 'MET':'M', 'PHE':'F', 'PRO':'P', 'SER':'S', 'THR':'T', 'TRP':'W', 'TYR':'Y', 'VAL':'V'}
df['MUTATION_CODE'] = df.WT_RESIDUE.map(codes)

Input

    WT_RESIDUE
0   ALA
1   REMARK
2   VAL
3   LYS

Output

    WT_RESIDUE  MUTATION_CODE
0   ALA          A
1   REMARK       NaN
2   VAL          V
3   LYS          K

answered Apr 27, 2021 at 3:33

Utsav

6,0932 gold badges36 silver badges58 bronze badges

1 Comment

paradocslover Over a year ago

Using map is the same as replace. Prior to version 19.2, a difference in speed was pointed but it seems to be no longer the case. Have a look at this - stackoverflow.com/questions/42012339/…

Collectives™ on Stack Overflow

.replace codes will not replace column with new column in python

2 Answers 2

Comments

1 Comment

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

Comments

1 Comment

Your Answer

Sign up or log in

Post as a guest

Linked

Related