Finding features of one geodataframe that contain at least one feature from another geodataframe

I have two polygon layers. One is a parcel layer (name "parcl") and the other one is a polygon layer (named "houses"). I am trying to find all parcels that contain at least one feature from the houses dataframe. I attempted to do so through a loop as shown below:

same = np.empty((0,parcl.shape[1]))

for i in parcl.index:
  for j in houses.index:
    a = parcl.loc[i]
    b = houses.loc[j]
    if (a.contains(b))==True:
      same.append(a)

Unfortunately, I got the following error message:

---------------------------------------------------------------------------

AttributeError                            Traceback (most recent call last)

<ipython-input-36-cedb059e5a3b> in <module>()
      5     a = parcl.loc[i]
      6     b = houses.loc[j]
----> 7     if (a.contains(b))==True:
      8       same.append(a)

/usr/local/lib/python3.7/dist-packages/pandas/core/generic.py in __getattr__(self, name)
   5139             if self._info_axis._can_hold_identifiers_and_holds_name(name):
   5140                 return self[name]
-> 5141             return object.__getattribute__(self, name)
   5142 
   5143     def __setattr__(self, name: str, value) -> None:

AttributeError: 'Series' object has no attribute 'contains'

Any help would be much appreciated! :)

Solution

This is a simple case of sjoin()

have simulated some houses (rectangles)
used some UK county definitions as parcels
gdf_contains which is result of sjoin() are now parcels that contain at least one house
visualised to demonstrate it has worked (green parcels)

import geopandas as gpd
import shapely.geometry
import numpy as np
import requests


world = gpd.read_file(gpd.datasets.get_path("naturalearth_lowres")).loc[lambda d: d["iso_a3"].eq("GBR")]
BOXES = 25
a, b, c, d = world.total_bounds

# manufactuer some houses
gdf_houses = gpd.GeoDataFrame(
    geometry=[
        shapely.geometry.box(minx, miny, maxx, maxy)
        for minx, maxx in zip(np.linspace(a, c, BOXES), np.linspace(a, c, BOXES)[1:])
        for miny, maxy in zip(np.linspace(b, d, BOXES), np.linspace(b, d, BOXES)[1:])
    ],
    crs="epsg:4326",
).sample(35)

gdf_houses.explore()
res = requests.get(
    "https://opendata.arcgis.com/datasets/37363d379f4f40fa8c3f0d28eedfdd37_0.geojson"
)
gdf_parcl = gpd.GeoDataFrame.from_features(res.json(), crs="epsg:4326")

gdf_contains = gdf_parcl.sjoin(gdf_houses)

m = gdf_parcl.explore(color="grey")
m = gdf_contains.explore(m=m, color="green")
m = gdf_houses.explore(m=m, style_kwds=dict(fillOpacity=.9))

m