import pandas as pd

def contains_code(crs_codes, code_list):
    codes = str(crs_codes).split(';')
    return any(code in code_list for code in codes)

def filter_all_projects(df, country_code_list, orga_code_list, crs3_list, crs5_list, sdg_str, region_list):
    # Check if filters where not all can be selected are empty
    if crs3_list or crs5_list or sdg_str:
        # FILTER CRS
        if crs3_list and not crs5_list:
            df = df[df['crs_3_code'].apply(lambda x: contains_code(x, crs3_list))]
        elif crs3_list and crs5_list:
            df = df[df['crs_5_code'].apply(lambda x: contains_code(x, crs5_list))]
        elif not crs3_list and crs5_list:
            df = df[df['crs_5_code'].apply(lambda x: contains_code(x, crs5_list))]

        # FILTER SDG
        if sdg_str:
            df = df[df["sgd_pred_code"] == int(sdg_str)]

    # FILTER COUNTRY
    if country_code_list:
        country_filtered_df = pd.DataFrame()
        for c in country_code_list:
            c_df = df[df["country"].str.contains(c, na=False)]
            country_filtered_df = pd.concat([country_filtered_df, c_df], ignore_index=False)
        df = country_filtered_df

    # FILTER REGION
    if region_list:
        df = df[df["region"].isin(region_list)]

    # FILTER ORGANIZATION
    if orga_code_list:
        df = df[df['orga_abbreviation'].isin(orga_code_list)]

    return df