add column to the csv file using python

Question

I have a big csv file with DNA sequences (sequence of characters) like this small example (infile.csv):

2840,GTGGCCCGGGAGGCC
291,GCATGTCCGTAGGTTCGT
147,GCATGTCCG

I need to translate each DNA sequence to peptide sequence (using the below function) and add the 3rd column which will be the peptide sequence. here is the expected output:

2840,GTGGCCCGGGAGGCC,VAREA
291,GCATGTCCGTAGGTTCGT,ACP*VR
147,GCATGTCCG,ACP

to do so, I made small following code:

import pandas
df = pandas.read_csv('infile.csv')
seq = csv_data[1]

def translate(seq):
    table = {
        'ATA':'I', 'ATC':'I', 'ATT':'I', 'ATG':'M',
        'ACA':'T', 'ACC':'T', 'ACG':'T', 'ACT':'T',
        'AAC':'N', 'AAT':'N', 'AAA':'K', 'AAG':'K',
        'AGC':'S', 'AGT':'S', 'AGA':'R', 'AGG':'R',
        'CTA':'L', 'CTC':'L', 'CTG':'L', 'CTT':'L',
        'CCA':'P', 'CCC':'P', 'CCG':'P', 'CCT':'P',
        'CAC':'H', 'CAT':'H', 'CAA':'Q', 'CAG':'Q',
        'CGA':'R', 'CGC':'R', 'CGG':'R', 'CGT':'R',
        'GTA':'V', 'GTC':'V', 'GTG':'V', 'GTT':'V',
        'GCA':'A', 'GCC':'A', 'GCG':'A', 'GCT':'A',
        'GAC':'D', 'GAT':'D', 'GAA':'E', 'GAG':'E',
        'GGA':'G', 'GGC':'G', 'GGG':'G', 'GGT':'G',
        'TCA':'S', 'TCC':'S', 'TCG':'S', 'TCT':'S',
        'TTC':'F', 'TTT':'F', 'TTA':'L', 'TTG':'L',
        'TAC':'Y', 'TAT':'Y', 'TAA':'*', 'TAG':'*',
        'TGC':'C', 'TGT':'C', 'TGA':'*', 'TGG':'W',
    }
    protein =""
    if len(seq)%3 == 0:
        for i in range(0, len(seq), 3):
            codon = seq[i:i + 3]
            protein+= table[codon]
    return protein


peptide_seq=translate(seq)
df[peptide_seq]
df.to_csv("outfile.csv")

but it does not return the expected output. do you know how I can change the code to get the expected output?

Please include a minimal reproducible example, which includes possible input data, the results and the expected results. — Ulrich Eckhardt
– Ulrich Eckhardt, Commented Sep 28, 2021 at 18:17

Алексей Р · Accepted Answer · 2021-09-28 18:16:10Z

import pandas

def translate(seq):
    table = {
        'ATA': 'I', 'ATC': 'I', 'ATT': 'I', 'ATG': 'M',
        'ACA': 'T', 'ACC': 'T', 'ACG': 'T', 'ACT': 'T',
        'AAC': 'N', 'AAT': 'N', 'AAA': 'K', 'AAG': 'K',
        'AGC': 'S', 'AGT': 'S', 'AGA': 'R', 'AGG': 'R',
        'CTA': 'L', 'CTC': 'L', 'CTG': 'L', 'CTT': 'L',
        'CCA': 'P', 'CCC': 'P', 'CCG': 'P', 'CCT': 'P',
        'CAC': 'H', 'CAT': 'H', 'CAA': 'Q', 'CAG': 'Q',
        'CGA': 'R', 'CGC': 'R', 'CGG': 'R', 'CGT': 'R',
        'GTA': 'V', 'GTC': 'V', 'GTG': 'V', 'GTT': 'V',
        'GCA': 'A', 'GCC': 'A', 'GCG': 'A', 'GCT': 'A',
        'GAC': 'D', 'GAT': 'D', 'GAA': 'E', 'GAG': 'E',
        'GGA': 'G', 'GGC': 'G', 'GGG': 'G', 'GGT': 'G',
        'TCA': 'S', 'TCC': 'S', 'TCG': 'S', 'TCT': 'S',
        'TTC': 'F', 'TTT': 'F', 'TTA': 'L', 'TTG': 'L',
        'TAC': 'Y', 'TAT': 'Y', 'TAA': '*', 'TAG': '*',
        'TGC': 'C', 'TGT': 'C', 'TGA': '*', 'TGG': 'W',
    }
    protein = ""
    if len(seq) % 3 == 0:
        for i in range(0, len(seq), 3):
            codon = seq[i:i + 3]
            protein += table[codon]
    return protein

# reading the csv without header, so columns names will be 0 and 1, then it makes the first column as index in df
df = pandas.read_csv('infile.csv', header=None, index_col=0)
# get the second column as Series and apply the function to each element
# result Series will be the new column 'peptide_seq'
df['peptide_seq'] = df[1].apply(translate)
# save the result df without header to get the target output
df.to_csv('outfile.csv', header=None)

Output:

2840,GTGGCCCGGGAGGCC,VAREA
291,GCATGTCCGTAGGTTCGT,ACP*VR
147,GCATGTCCG,ACP

Your answer would be so much better if you actually explain what you're doing differently and why, instead of just "this will work".

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