Merge pull request #615 from cmu-delphi/safegraph-pattens-hhrnation

Add nation and HHS to Safegraph patterns

Author: krivard

safegraph_patterns/DETAILS.md

@@ -2,7 +2,7 @@
 
 We import Zip Code-level raw mobility indicators from SafeGraph **Weekly 
 Patterns** dataset, calculate functions of the raw data, and then aggregate 
-he data to the county, hrr, msa and state levels.
+he data to the county, hrr, msa, hhs, nation, and state levels.
 
 ## Brand Information
 SafeGraph provides daily number of visits to points of interest (POIs) in Weekly
@@ -22,6 +22,8 @@ new necessary `brand_info.csv` in `./statics` with suffix YYYYMM(release version
 * `msa`: reported using CBSA (consistent with all other COVIDcast sensors)
 * `hrr`: reported using HRR number (consistent with all other COVIDcast sensors)
 * `state`: reported using two-letter postal code
+* `hhs`: reported using HHS region number
+* `nation`: reported using two-letter country abbreviation. Just `us` for now.
 
 ## Metrics,  Level 1 (`m1`)
 * `bars_visit`: The number of visits to bars(places with NAICS code = 722410)

safegraph_patterns/README.md

@@ -2,7 +2,7 @@
 
 We import raw mobility data from Safegraph Weekly Patterns, calculate some 
 statistics upon it, and aggregate the data from the Zip Code level to County,
-HRR, MSA and State levels. For detailed information see the files `DETAILS.md` 
+HRR, MSA, HHS, Nation, and State levels. For detailed information see the files `DETAILS.md` 
 contained in this directory.
 
 ## Running the Indicator

safegraph_patterns/delphi_safegraph_patterns/process.py

@@ -14,7 +14,9 @@
         "county": "fips",
         "msa": "msa",
         "hrr": "hrr",
-        "state": "state_id"
+        "state": "state_id",
+        "hhs": "hhs",
+        "nation": "nation"
 }
 
 def construct_signals(df, metric_names, naics_codes, brand_df):
@@ -97,7 +99,7 @@ def aggregate(df, metric, geo_res):
     metric: str
         Name of metric to be exported.
     geo_resolution: str
-        One of ('county', 'hrr, 'msa', 'state')
+        One of ('county', 'hrr, 'msa', 'state', 'hhs', 'nation')
 
     Returns
     -------
@@ -112,9 +114,7 @@ def aggregate(df, metric, geo_res):
     gmpr = GeoMapper()
     geo_key = GEO_KEY_DICT[geo_res]
     df = gmpr.add_population_column(df, "zip")
-    df = gmpr.replace_geocode(df, "zip", geo_key,
-                              date_col="timestamp",
-                              data_cols=[metric_count_name, "population"])
+    df = gmpr.replace_geocode(df, "zip", geo_key, date_col="timestamp", data_cols=[metric_count_name, "population"])
 
     df[metric_prop_name] = df[metric_count_name] / df["population"] \
                             * INCIDENCE_BASE

safegraph_patterns/delphi_safegraph_patterns/run.py

@@ -35,6 +35,8 @@
         "hrr",
         "msa",
         "state",
+        "hhs",
+        "nation"
 ]