Reformat.

src/features/phone_esm/straw/preprocess.py

@@ -1,21 +1,21 @@
 import json
+
 import numpy as np
 import pandas as pd
 
-
 ESM_TYPE = {
-        "text": 1,
-        "radio": 2,
-        "checkbox": 3,
-        "likert": 4,
-        "quick_answers": 5,
-        "scale": 6,
-        "datetime": 7,
-        "pam": 8,
-        "number": 9,
-        "web": 10,
-        "date": 11,
-    }
+    "text": 1,
+    "radio": 2,
+    "checkbox": 3,
+    "likert": 4,
+    "quick_answers": 5,
+    "scale": 6,
+    "datetime": 7,
+    "pam": 8,
+    "number": 9,
+    "web": 10,
+    "date": 11,
+}
 
 ESM_STATUS_ANSWERED = 2
 
@@ -101,7 +101,7 @@ def clean_up_esm(df_esm_preprocessed: pd.DataFrame) -> pd.DataFrame:
 
 df_esm = pd.read_csv(snakemake.input[0])
 df_esm_preprocessed = preprocess_esm(df_esm)
-#TODO Enable getting the right questionnaire here.
+# TODO Enable getting the right questionnaire here.
 df_esm_PANAS = df_esm_preprocessed[
     (df_esm_preprocessed["questionnaire_id"] == 8)
     | (df_esm_preprocessed["questionnaire_id"] == 9)
@@ -109,5 +109,3 @@ df_esm_PANAS = df_esm_preprocessed[
 df_esm_clean = clean_up_esm(df_esm_PANAS)
 
 df_esm_clean.to_csv(snakemake.output[0])
-
-