From cca5a294833d6766663afa43b6c1c84c58c4cd50 Mon Sep 17 00:00:00 2001
From: junos <junos.lukan@ijs.si>
Date: Fri, 6 Aug 2021 18:51:13 +0200
Subject: [PATCH] Rename features and add one for missed calls.

---
 features/communication.py | 37 ++++++++++++++++++++++---------------
 1 file changed, 22 insertions(+), 15 deletions(-)

diff --git a/features/communication.py b/features/communication.py
index a3c917c..0c44259 100644
--- a/features/communication.py
+++ b/features/communication.py
@@ -255,14 +255,16 @@ def calls_sms_features(df_calls: pd.DataFrame, df_sms: pd.DataFrame) -> pd.DataF
     df_calls_sms: pd.DataFrame
         The list of features relating calls and sms data for every participant.
         These are:
-        * no_calls_no_sms_ratio:
+        * proportion_calls:
             proportion of calls in total number of communications
-        * no_incoming_calls_no_recieved_sms_ratio:
+        * proportion_calls_incoming:
             proportion of incoming calls in total number of incoming/recieved communications
-        * no_outgoing_calls_no_sent_sms_ratio:
+        * proportion_calls_outgoing:
             proportion of outgoing calls in total number of outgoing/sent communications
-        * no_calls_contacts_no_sms_contacts_ratio:
-            proportion of calls contacts in total number of communication contacts 
+        * proportion_calls_missed_sms_received:
+            proportion of missed calls to the number of received messages
+        * proportion_calls_contacts:
+            proportion of calls contacts in total number of communication contacts
     """
 
     count_calls = count_comms(df_calls)
@@ -274,20 +276,25 @@ def calls_sms_features(df_calls: pd.DataFrame, df_sms: pd.DataFrame) -> pd.DataF
         )  # Merge calls and sms features
         .reset_index()  # Make participant_id a regular column
         .assign(
-            no_calls_no_sms_ratio=(
+            proportion_calls=(
                 lambda x: x.no_all_calls / (x.no_all_calls + x.no_all_sms)
             ),
-            no_incoming_calls_no_recieved_sms_ratio=(
-                lambda x: x.no_received / (x.no_incoming + x.no_received)
+            proportion_calls_incoming=(
+                lambda x: x.no_incoming / (x.no_incoming + x.no_received)
             ),
-            no_outgoing_calls_no_sent_sms_ratio=(
+            proportion_calls_missed_sms_received=(
+                lambda x: x.no_missed / (x.no_missed + x.no_received)
+            ),
+            proportion_calls_outgoing=(
                 lambda x: x.no_outgoing / (x.no_outgoing + x.no_sent)
-            )  # Calculate new features and create additional columns
+            )
+            # Calculate new features and create additional columns
         )[
             ["participant_id",
-             "no_calls_no_sms_ratio",
-             "no_incoming_calls_no_recieved_sms_ratio",
-             "no_outgoing_calls_no_sent_sms_ratio"]
+             "proportion_calls",
+             "proportion_calls_incoming",
+             "proportion_calls_outgoing",
+             "proportion_calls_missed_sms_received"]
         ]  # Filter out only the relevant feautres
     )
 
@@ -300,13 +307,13 @@ def calls_sms_features(df_calls: pd.DataFrame, df_sms: pd.DataFrame) -> pd.DataF
         )  # Merge calls and sms features
         .reset_index()  # Make participand_id a regular column
         .assign(
-            no_calls_contacts_no_sms_contacts_ratio=(
+            proportion_calls_contacts=(
                 lambda x: x.no_contacts_calls /
                     (x.no_contacts_calls + x.no_contacts_sms)
             )  # Calculate new features and create additional columns
         )[
             ["participant_id",
-             "no_calls_contacts_no_sms_contacts_ratio"]
+             "proportion_calls_contacts"]
         ]  # Filter out only the relevant feautres
         # Since we are interested only in some features and ignored
         # others, a lot of duplicate rows were created. Remove them.