Convert values of an entire column in a datafarme pandas - pandas

Question

I have the following dataframe:
chr start_position end_position gene_name
0 Chr Position Ref Gene_Name
1 chr22 24128945 G nan
2 chr19 45867080 G ERCC2
3 chr3 52436341 C BAP1
4 chr7 151875065 G KMT2C
5 chr19 1206633 CGGGT STK11
and I'd like to convert the entire 'end_position' column to contain the values of the 'start_position'+len('end_position'), the results should be:
chr start_position end_position gene_name
0 Chr Position Ref Gene_Name
1 chr22 24128945 24128946 nan
2 chr19 45867080 45867081 ERCC2
3 chr3 52436341 52436342 BAP1
4 chr7 151875065 151875066 KMT2C
5 chr19 1206633 1206638 STK11
I have written the below script:
patient_vcf_to_df.apply(pd.to_numeric, errors='ignore')
patient_vcf_to_df['end_position'] = patient_vcf_to_df['end_position'].map(lambda x: patient_vcf_to_df['start_position'] + len(x))
but I got the error:
TypeError: must be str, not int
Anyone knows how can I fix the problem?
Thanks a lot!

Answer 1

first I'd read your CSV in a way that the 0 row would become a header (column names):
df = pd.read_csv(filename, header=1)
to get the following DF:
Chr Position Ref Gene_Name
0 chr22 24128945 G NaN
1 chr19 45867080 G ERCC2
2 chr3 52436341 C BAP1
3 chr7 151875065 G KMT2C
4 chr19 1206633 CGGGT STK11
as a positive side-effect:
In [99]: df.dtypes
Out[99]:
chr object
position int64 # <--- NOTE
ref object
gene_name object
dtype: object
if you want to lower-case your columns:
In [97]: df.columns = df.columns.str.lower()
In [98]: df
Out[98]:
chr position ref gene_name
0 chr22 24128945 G NaN
1 chr19 45867080 G ERCC2
2 chr3 52436341 C BAP1
3 chr7 151875065 G KMT2C
4 chr19 1206633 CGGGT STK11
to make sure that position column is of a numeric dtype:
df['position'] = pd.to_numeric(df['position'], errors='coerce')
and then:
In [101]: df['end_position'] = df['position'] + df['ref'].str.len()
In [102]: df
Out[102]:
chr position ref gene_name end_position
0 chr22 24128945 G NaN 24128946
1 chr19 45867080 G ERCC2 45867081
2 chr3 52436341 C BAP1 52436342
3 chr7 151875065 G KMT2C 151875066
4 chr19 1206633 CGGGT STK11 1206638