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def get_category_tree(df, category_dict, category_id):
    if category_id is np.nan:
        return ''

    tree = []
    tree.insert(0, category_dict[category_id])
    
    def get_tree(df, category_dict, category_id):
        parent_id = df[df['category_id'] == category_id]['parent_category_id'].values[0]
        if parent_id is np.nan:
            return ' -> '.join(tree)
        else:
            tree.insert(0, category_dict[parent_id])
            return get_tree(df, category_dict, parent_id)
            
    return get_tree(df, category_dict, category_id)

x_cat_df = pd.read_csv('~/Downloads/Shopify ICP categories - categories_raw.csv')
x_categories = dict(zip(x_cat_df['category_id'], x_cat_df['category_name']))

def add_x_category_tree(row):
    return get_category_tree(x_cat_df, x_categories, row['category_id'])

x_cat_df['category_tree'] = x_cat_df.apply(add_x_category_tree, axis=1)