diff --git a/google_symptoms/delphi_google_symptoms/constants.py b/google_symptoms/delphi_google_symptoms/constants.py
index 06f9187d8..0173b7d40 100644
--- a/google_symptoms/delphi_google_symptoms/constants.py
+++ b/google_symptoms/delphi_google_symptoms/constants.py
@@ -80,4 +80,4 @@
                    'Wisconsin': 'wi',
                    'Wyoming': 'wy'}
 
-DC_FIPS = "11001"
\ No newline at end of file
+DC_FIPS = "11001"
diff --git a/google_symptoms/delphi_google_symptoms/geo.py b/google_symptoms/delphi_google_symptoms/geo.py
index 257ff884f..99bba48ec 100644
--- a/google_symptoms/delphi_google_symptoms/geo.py
+++ b/google_symptoms/delphi_google_symptoms/geo.py
@@ -21,7 +21,7 @@ def generate_transition_matrix(geo_res):
         The first is a data frame for HRR regions and the second are MSA
         regions.
     """
-    map_df = gmpr._load_crosswalk("fips", geo_res)
+    map_df = gmpr._load_crosswalk("fips", geo_res)  # pylint: disable=protected-access
     # Add population as weights
     map_df = gmpr.add_population_column(map_df, "fips")
     if geo_res == "hrr":
@@ -31,7 +31,7 @@ def generate_transition_matrix(geo_res):
             msa_pop, on=geo_res, how="inner", suffixes=["_raw", "_groupsum"]
             )
     map_df["weight"] = map_df["population_raw"] / map_df["population_groupsum"]
- 
+
     map_df = pd.pivot_table(
                  map_df, values='weight', index=["fips"], columns=[geo_res]
               ).fillna(0).reset_index().rename({"fips": "geo_id"}, axis = 1)
@@ -52,13 +52,13 @@ def geo_map(df, geo_res):
     Returns
     -------
     pd.DataFrame
-        A dataframe with columns "geo_id", "timestamp", 
-        and columns for signal vals. 
+        A dataframe with columns "geo_id", "timestamp",
+        and columns for signal vals.
         The geo_id has been converted from fips to HRRs/MSAs
     """
     if geo_res in set(["county", "state"]):
         return df
-    
+
     map_df = generate_transition_matrix(geo_res)
     converted_df = pd.DataFrame(columns = df.columns)
     for _date in df["timestamp"].unique():
@@ -75,4 +75,4 @@ def geo_map(df, geo_res):
         newdf[mask] = np.nan
         converted_df = converted_df.append(newdf)
     return converted_df
-    
\ No newline at end of file
+    
diff --git a/google_symptoms/delphi_google_symptoms/pull.py b/google_symptoms/delphi_google_symptoms/pull.py
index 85aacf194..10b540c88 100644
--- a/google_symptoms/delphi_google_symptoms/pull.py
+++ b/google_symptoms/delphi_google_symptoms/pull.py
@@ -43,7 +43,7 @@ def preprocess(df, level):
     """
     # Constants
     KEEP_COLUMNS = ["geo_id", "date"] + METRICS + ["combined_symptoms"]
-    
+
     df["combined_symptoms"] = 0
     for metric in METRICS:
         df.rename({"symptom:" + metric: metric}, axis = 1, inplace = True)
@@ -52,7 +52,7 @@ def preprocess(df, level):
             (df["Anosmia"].isnull())
             & (df["Ageusia"].isnull())
             , "combined_symptoms"] = np.nan
-  
+
     # Delete rows with missing FIPS
     null_mask = (df["geo_id"].isnull())
     df = df.loc[~null_mask]
diff --git a/google_symptoms/delphi_google_symptoms/run.py b/google_symptoms/delphi_google_symptoms/run.py
index 9634c80c7..170816c9a 100644
--- a/google_symptoms/delphi_google_symptoms/run.py
+++ b/google_symptoms/delphi_google_symptoms/run.py
@@ -23,7 +23,7 @@ def run_module():
     base_url = params["base_url"]
 
     # Pull GS data
-    dfs = pull_gs_data(base_url)    
+    dfs = pull_gs_data(base_url)
     for geo_res in GEO_RESOLUTIONS:
         if geo_res == "state":
             df_pull = dfs["state"]
@@ -48,4 +48,4 @@ def run_module():
                 start_date=SMOOTHERS_MAP[smoother][1](export_start_date),
                 metric=metric.lower(),
                 geo_res=geo_res,
-                sensor=sensor_name)
\ No newline at end of file
+                sensor=sensor_name)