When looping though a dataframe looking for string values. How do I print out rows without duplicating if the search term is found multiple times?

Question

I am importing pandas and reading a csv file.

import pandas as pd

df = pd.read_csv(r'C:\Users\Me\MyFile.csv')

I am converting the dataframe to strings and making the contents lowercase

df_low = df.apply(lambda x: x.astype(str).str.lower() if (x.dytpe == 'object'_ else x)

I'm using user input to search for strings

searchterm = str(input("Enter search term: ").lower())

looping through the dataframe and creating mask, then only returning non-empty results. I'm currently using the .upper command only due to the 'Item Number' having 3 capital letters in the beginning but, of course this is making the entire output capital but that is workable.

for item in df_low:
    mask = df_low[item].str.contains(searchterm)
    df_mask = pd.DataFrame(df_low[mask])
    if not df_mask.empty:
        print(df_mask[['Item Number', 'User Name', 'Short Description']].to_string(index=false).upper())

if df contains the following:

Item Number	User Name	Short Description	Comments
ITM-1	Leonardo	words and stuff	I wrote words
ITM-2	Donatello	guy and words	N/A
ITM-3	Frank	Technology list	Technology stack

Searching for the term 'technology' Expected Output:

Item Number	User Name	Short Description
ITM-3	FRANK	TECHNOLOGY LIST

Due to the loop, the actual output would be the following since the search term is found in both the 'Short Description and 'Comments' fields:

Item Number	User Name	Short Description
ITM-3	FRANK	TECHNOLOGY LIST

Item Number	User Name	Short Description
ITM-3	FRANK	TECHNOLOGY LIST

I tried multiple variations of .drop_duplicates but I know enough to know I don't know how to use that because I have a limited understanding where that would go in the overall code.

Answer 1

Instead of a loop, you can use applymap to filter rows that have the searchterm in any column:

searchterm = "Technology"

out = df[
    df.applymap(lambda x: isinstance(x, str) and searchterm.lower() in x.lower())
    .any(axis=1)
]
out = out[["Item Number", "User Name", "Short Description"]]

  Item Number User Name Short Description
2       ITM-3     Frank   Technology list