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j40-cejst-2/data/data-pipeline/data_pipeline/ipython/geojson_compare_tiles.ipynb
Lucas Merrill Brown 6e6223cd5e
Issue 105: Configure and run black and other pre-commit hooks (clean branch) (#1962) 
* Configure and run `black` and other pre-commit hooks

Co-authored-by: matt bowen <matthew.r.bowen@omb.eop.gov>
2022-10-04 18:08:47 -04:00

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{
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{
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"id": "27da604f",
"metadata": {},
"outputs": [],
"source": [
"# %load_ext lab_black\n",
"import json\n",
"import pandas as pd\n",
"import geopandas as gpd\n",
"\n",
"# Read in the above json file\n",
"nation = gpd.read_file(\"/Users/vims/Downloads/usa-high-1822-637b.json\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "7b7083fd",
"metadata": {},
"outputs": [
{
"data": {
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"0 None\n",
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"Name: FUDS_RAW, Length: 74134, dtype: object"
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},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nation[\"FUDS_RAW\"]"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "117477e6",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>GEOID10</th>\n",
" <th>SF</th>\n",
" <th>CF</th>\n",
" <th>HRS_ET</th>\n",
" <th>AML_ET</th>\n",
" <th>AML_RAW</th>\n",
" <th>FUDS_ET</th>\n",
" <th>FUDS_RAW</th>\n",
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" <th>0</th>\n",
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" <td>Minnesota</td>\n",
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" <td>False</td>\n",
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" <td>Idaho</td>\n",
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],
"text/plain": [
" GEOID10 SF CF HRS_ET AML_ET AML_RAW FUDS_ET \\\n",
"0 27139080202 Minnesota Scott County None False None False \n",
"1 27139080204 Minnesota Scott County None False None False \n",
"2 27139080100 Minnesota Scott County None False None False \n",
"3 27139080302 Minnesota Scott County None False None False \n",
"4 27139080400 Minnesota Scott County None False None False \n",
"... ... ... ... ... ... ... ... \n",
"74129 16005001601 Idaho Bannock County None False None False \n",
"74130 16005001300 Idaho Bannock County None False None False \n",
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"74132 16005000900 Idaho Bannock County None False None False \n",
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"\n",
" FUDS_RAW \n",
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"1 None \n",
"2 None \n",
"3 None \n",
"4 None \n",
"... ... \n",
"74129 None \n",
"74130 None \n",
"74131 None \n",
"74132 None \n",
"74133 None \n",
"\n",
"[74134 rows x 8 columns]"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nation_new_ind = nation[\n",
" [\n",
" \"GEOID10\",\n",
" \"SF\",\n",
" \"CF\",\n",
" \"HRS_ET\",\n",
" \"AML_ET\",\n",
" \"AML_RAW\",\n",
" \"FUDS_ET\",\n",
" \"FUDS_RAW\",\n",
" ]\n",
"]\n",
"nation_new_ind"
]
},
{
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"id": "0f37acf4",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([None, '0', '1'], dtype=object)"
]
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nation_new_ind[\"HRS_ET\"].unique()"
]
},
{
"cell_type": "code",
"execution_count": 69,
"id": "4ae865ae",
"metadata": {},
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{
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"0 8843\n",
"1 4045\n",
"Name: HRS_ET, dtype: int64"
]
},
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nation_new_ind[\"HRS_ET\"].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "2f0d29db",
"metadata": {},
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{
"data": {
"text/plain": [
"array([False, True])"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nation_new_ind[\"AML_ET\"].unique()"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "646b3754",
"metadata": {},
"outputs": [
{
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"False 72100\n",
"True 2034\n",
"Name: AML_ET, dtype: int64"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nation_new_ind[\"AML_ET\"].value_counts()"
]
},
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"source": [
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{
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"id": "370b0769",
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"source": [
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"id": "f8afb668",
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"nation_new_ind[\"FUDS_RAW\"].unique()"
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{
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"id": "b722e802",
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"0 3170\n",
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],
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}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
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},
"language_info": {
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"file_extension": ".py",
"mimetype": "text/x-python",
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"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
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