Cleaning my code to make it more efficient

[deanhystad]

I think your approach is all wrong. Instead of testing each column for a filter, you should make a list of filters to apply. Filtering can be done with a compact loop that loops through all the selected filters.

The example below uses a dictionary to map column names with column values.

import pandas as pd
from dataclasses import dataclass
from random import choices


# Make a dataframe for demonstrating filter.
letters = list("ABCDEIOU")
numbers = list(range(1, 10))
mixed = [f"{letter}{number}" for letter in letters for number in numbers]


df = pd.DataFrame(
    {
        "Letters": choices(letters, k=20),
        "Numbers": choices(numbers, k=20),
        "Mixed": choices(mixed, k=20),
    }
)


def filter(frame, filters):
    """Apply filters to dataframe.  filters is a dictionary of column: values pairs."""
    df = frame.copy()
    for key, value in filters.items():
        df = df[df[key].isin(value)]
    return df


print("Numbers = 7", filter(df, {"Numbers": [7]}), sep="\n")
odd_abcs = {"Numbers": [1, 3, 5, 7, 9], "Letters": ["A", "B", "C"]}
print("", "Odd ABC's", filter(df, odd_abcs), sep="\n")
even_vowels = {}
even_vowels["Numbers"] = [2, 4, 6, 8]
even_vowels["Letters"] = ["A", "E", "I", "O", "U"]
print("", "Even Vowels", filter(df, even_vowels), sep="\n")