根据约束从 Pandas DataFrame 中选择行

Question

I have several datasets that I import as csv files and display them in a DataFrame in Pandas. The csv files are info about Covid updates.

The datasets has several columns relating to this, for example "country_region", "last_update" & "confirmed".

Let's say I wanted to look up the confirmed cases of Covid for Germany.

I'm trying to write a function that will return a slice of the DataFrame that corresponds to those constraints to be able to display the match I'm looking for.

I need to do this in some generic way so I can provide any value from any column.

I wish I had some code to include but I'm stuck on how to even proceed. Everything I find online only specifies for looking up values relating to a pre-defined value.

Answer 1

Something like this?

def filter(county_region_val, last_update_val, confirmed_val, df):
    df = df.loc[((df['county_region'] == county_region_val) & (df['last_update'] == last_update_val) & (df[''confirmed'] == confirmed_val)).reset_index(drop=True)
    return df