CODEWITHSUNDEEP
pythondataframe
upendra
upendra

Reputation: 2189

How can I replace a column given a specific condition in python?

I have a dataframe that contains multiple columns as below...

Chr1    Cufflinks   exon    28354206    28354551    .   .   .   gene_id "XLOC_008369"; transcript_id "TCONS_00014347"; exon_number "1"; oId "CUFF.2405.1"; class_code "u"; tss_id "TSS10073";
Chr1    Cufflinks   exon    28785549    28786194    .   .   .   gene_id "XLOC_008370"; transcript_id "TCONS_00014348"; exon_number "1"; oId "CUFF.2441.1"; class_code "u"; tss_id "TSS10074";
Chr1    Cufflinks   exon    29328712    29329210    .   .   .   gene_id "XLOC_008371"; transcript_id "TCONS_00014349"; exon_number "1"; oId "CUFF.2495.1"; class_code "u"; tss_id "TSS10075";
Chr1    Cufflinks   exon    29427951    29428406    .   .   .   gene_id "XLOC_008372"; transcript_id "TCONS_00014350"; exon_number "1"; oId "CUFF.2506.1"; class_code "u"; tss_id "TSS10076";
Chr1    Cufflinks   exon    29460116    29460585    .   .   .   gene_id "XLOC_008373"; transcript_id "TCONS_00014351"; exon_number "1"; oId "CUFF.2509.1"; class_code "u"; tss_id "TSS10077";

What i am trying to do is, if any of the items in my list is present in one of the column of the dataframe, then i replace the 2nd column from Cufflinks to lincRNA.

One problem is the column that i am using for making the key in the dictionary has multiple rows in the dataframe and because of that i am getting only unique key and so the total number of rows that are outputted are not the same as the input.

Here is my code so far...

#!/usr/bin/env python

file_in = open("lincRNA_final_transcripts.fa")
file_in2 = open("AthalianaslutteandluiN30merged.gtf")
file_out = open("updated.gtf", 'w')

sites = []
result = {}

for line in file_in:
    line = line.strip()
    if line.startswith(">"):
        line = line[1:]
        gene = str.split(line, ".")
        gene = gene[0]
        sites.append(gene)


for line2 in file_in2:
    line2 = line2.strip().split()
    line3 = str.split(line2[11], ";")
    line3 = line3[0]
    line3 = line3[1:-1]
    result[line3] = line2


for id in sites:
    id2 = str(id)
    if id2 in result.keys():
        result[id][1] = "lincRNA"

for val in result.values():
    file_out.write("\t".join(val))
    file_out.write("\n")

Upvotes: 0

Views: 189

Answers (1)

ilyas patanam
ilyas patanam

Reputation: 5324

I'll try to give a walkthrough of how you would do this in pandas. Pandas is a python library for handling dataframes and learning it makes it easy to do dataframe manipulations.

  1. Install pandas

    sudo pip install pandas

  2. Load your data into a pandas dataframe object. It seems gtf is a tab delimited file, so pass \t as the separator. If there is no header line pass None, if the first line is a header then pass 0 instead. For more information on the parameters, see here.

    import pandas
df = pd.read_csv('AthalianaslutteandluiN30merged.gtf', sep = '\t', header = None, engine = 'python')

    0      1             2       3       4     5 6 7            8  
0   Chr1    Cufflinks   exon 28354206 28354551 . . .    gene_id "XLOC_008369"   transcript_id "TCONS_00014347"  exon_number "1" oId "CUFF.2405.1"   class_code "u"  tss_id "TSS10073"
1   Chr1    Cufflinks   exon 28785549 28786194 . . .    gene_id "XLOC_008370"   transcript_id "TCONS_00014348"  exon_number "1" oId "CUFF.2441.1"   class_code "u"  tss_id "TSS10074"

  3. Check if the strings in column 8 contain a substring that is also contained in your sites list. We will use this idea.

    sites = ["XLOC_008369", "XLOC_008369"]
pattern = '|'.join(sites)
mask = df[8].str.contains(pattern)

  4. Use boolean indexing to change Cufflinks to lincRNA if column 8 contains a substring that matches with an element in sites list. See here, for more on pandas indexing.

    df.loc[mask,1] = 'lincRNA'

EDIT: Use str.contains to check if a pandas column contains an element in the list.

Upvotes: 2

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