| 
52 | 52 |     "from calitp_data_analysis.tables import tbls\n",  | 
53 | 53 |     "from siuba import *\n",  | 
54 | 54 |     "\n",  | 
55 |  | -    "from calitp_data_analysis import geography_utils\n",  | 
56 |  | -    "from shared_utils import geography_utils, utils"  | 
 | 55 | +    "from calitp_data_analysis import geography_utils, utils\n",  | 
 | 56 | +    "from shared_utils import portfolio_utils"  | 
57 | 57 |    ]  | 
58 | 58 |   },  | 
59 | 59 |   {  | 
 | 
424 | 424 |     "count_cols = [\"pickup\"]\n",  | 
425 | 425 |     "nunique_cols = [\"pickup_zone\"]\n",  | 
426 | 426 |     "\n",  | 
427 |  | -    "by_borough = geography_utils.aggregate_by_geography(\n",  | 
 | 427 | +    "by_borough = portfolio_utils.aggregate_by_geography(\n",  | 
428 | 428 |     "    df[df.pickup_borough.notna()], \n",  | 
429 | 429 |     "    group_cols=group_cols,\n",  | 
430 | 430 |     "    sum_cols = sum_cols,\n",  | 
 | 
749 | 749 |     }  | 
750 | 750 |    ],  | 
751 | 751 |    "source": [  | 
752 |  | -    "df2 = geography_utils.aggregate_by_geography(\n",  | 
 | 752 | +    "df2 = portfolio_utils.aggregate_by_geography(\n",  | 
753 | 753 |     "    df[(df.payment.notna()) & (df.pickup_borough.notna())], \n",  | 
754 | 754 |     "    group_cols = [\"pickup_borough\", \"payment\"],\n",  | 
755 | 755 |     "    sum_cols = [\"passengers\", \"fare\"],\n",  | 
 | 
981 | 981 |    "source": [  | 
982 | 982 |     "import branca\n",  | 
983 | 983 |     "import geopandas as gpd\n",  | 
984 |  | -    "import pandas as pd\n",  | 
985 |  | -    "\n",  | 
986 |  | -    "from calitp_data_analysis import geography_utils"  | 
 | 984 | +    "import pandas as pd"  | 
987 | 985 |    ]  | 
988 | 986 |   },  | 
989 | 987 |   {  | 
 | 
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