Merge pull request #377 from cmu-delphi/usafacts-docs

Update usafacts docstrings to pass pydocstyle

Author: krivard

usafacts/delphi_usafacts/geo.py

@@ -61,8 +61,7 @@ def disburse(df: pd.DataFrame, pooled_fips: str, fips_list: list):
 
 def geo_map(df: pd.DataFrame, geo_res: str, map_df: pd.DataFrame, sensor: str):
     """
-    Maps a DataFrame df, which contains data at the county resolution, and
-    aggregate it to the geographic resolution geo_res.
+    Map a DataFrame with county level data and aggregate it to the geographic resolution geo_res.
 
     Parameters
     ----------

usafacts/delphi_usafacts/pull.py

@@ -14,7 +14,7 @@
 
 
 def pull_usafacts_data(base_url: str, metric: str, geo_mapper: GeoMapper) -> pd.DataFrame:
-    """Pulls the latest USA Facts data, and conforms it into a dataset
+    """Pull the latest USA Facts data, and conform it into a dataset.
 
     The output dataset has:
 
@@ -53,7 +53,6 @@ def pull_usafacts_data(base_url: str, metric: str, geo_mapper: GeoMapper) -> pd.
     pd.DataFrame
         Dataframe as described above.
     """
-
     # Read data
     df = pd.read_csv(base_url.format(metric=metric)).rename({"countyFIPS":"FIPS"}, axis=1)
     # Check missing FIPS

usafacts/delphi_usafacts/smooth.py

@@ -1,9 +1,10 @@
-'''Functions for smoothing signals.'''
+"""Functions for smoothing signals."""
 # -*- coding: utf-8 -*-
+"""Smoothing functions."""
 import numpy as np
 
 def identity(x):
-    '''Trivial "smoother" that does no smoothing.
+    """Trivial "smoother" that does no smoothing.
 
     Parameters
     ----------
@@ -14,11 +15,11 @@ def identity(x):
     -------
     np.ndarray:
         Same as x
-    '''
+    """
     return x
 
 def kday_moving_average(x, k):
-    '''Compute k-day moving average on x.
+    """Compute k-day moving average on x.
 
     Parameters
     ----------
@@ -29,7 +30,7 @@ def kday_moving_average(x, k):
     -------
     np.ndarray:
         k-day moving average.  The first k-1 entries are np.nan.
-    '''
+    """
     if not isinstance(k, int):
         raise ValueError('k must be int.')
     # temp = np.append(np.zeros(k - 1), x)