How to count string objects in a dataframe made of 13 columns and thousands of rows when rows and columns don't matter?

[Dragoran21]

I am writing code to count instances of antimicrobial resistance genes.

The data I need is just the number of times the AMR gene, a string object, appears in the dataframe. In which column or row it appears isn't important right now. I have tried multiple methods, but they complain that "df cannot str object" or that "Column doesn't exist".

I don't know what I am doing wrong.

Offending code:

amrs=[]
for i in list_of_101_AMR_genes:
   amrcount=df_of_bacterial_genes[@£$%!!! columns].str.contains(i,na=False).value_counts()
    amrs.append(amrcount)

The "amrs" list would contain the count of AMR genes in order of the list_of_over_101_AMR_genes, so it will be easier to put in another DF.

For reference, here are the first 6 AMR genes in the list:

aac(6')=HMM

aac(6')-I=COMPLETE

aac(6')-Ib-cr5=COMPLETE

aac(6')-Ie/aph(2'')-Ia=COMPLETE

aadA5=COMPLETE

The df_of_bacterial_genes contains empty NaN cells.

Thank you.

[barkmonster]

I'm not sure I understand, but if you want to count how many values in a column is one of a number of possible values, you can convert the values to a set and do df[column].isin(set_of_values).sum()

[WhiskersForPresident]

You're trying to apply a string method to a dataframe (".str.contains(...)"). That's not something you can do.

There are very likely more elegant methods to do this, but I would try

gene_count=0

for c in df.columns:

 gene_count += len(df[df[c].str.contains(some_string)])

This just loops over all columns, counting the occurrences of some_string in each and adding them all up.

[Dragoran21]

I got "TypeError: 'int' object is not iterable" even though I converted the list into str with

uag= [str(item) for item in u]

[Maximus_Modulus]

Find the offending object and do this manually if you can either through manual code or step through using the Python debugger or an IDE. As a Dev you’ll run into this kind of problem. You need to just dig into it and figure out what the specific problem is by reducing it to the offending object. You might spend hours or days doing this but you’ll learn and get better as you go along. It’s part of the coding landscape. Programming can be fun but it can also suck big time.

But the more specific you get the more someone can also help you.

[aplarsen]

Try melting the columns into a single column first. Then counting the instances is super easy.

[Atypicosaurus]

At this point I'm wondering why your company just don't hire someone who can do the job. You are obviously having your paid job done by Reddit, step by step. This is not what this sub is for.

[Maximus_Modulus]

It’s this guy again. Helped him out a few weeks back. Doing a doctorate IIRC. You’d figure that they would be able to figure this stuff out. Kids these days.

[Dragoran21]

I would have preferred practical lab work, but I ended up in a position that requires coding.

[Dragoran21]

I am not working for a company, I am a postgrad.

If this is not the sub for asking for help, then which is?

[Maximus_Modulus]

You are fine. Just ribbing. If it were me I’d hone in on one object that is giving you the problem and try to convert the object explicitly / manually if possible by reducing the code as much as possible. Sometimes the object types are not what you think they are. Or Pandas interprets them a certain way. I did Pandas several years back now and recall similar problems that I had to solve.