From 78a9d82a7480584e93fe63f45db66b99fded108b Mon Sep 17 00:00:00 2001 From: nikunjgoel95 Date: Sun, 21 Jun 2020 16:49:29 -0400 Subject: [PATCH] Modified the UNIX time to minutes from Midnight in timeFirstConversation and timeLastConversation --- src/features/conversation/conversation_base.py | 14 +++++++++++--- 1 file changed, 11 insertions(+), 3 deletions(-) diff --git a/src/features/conversation/conversation_base.py b/src/features/conversation/conversation_base.py index fb1fd103..5e99b25d 100644 --- a/src/features/conversation/conversation_base.py +++ b/src/features/conversation/conversation_base.py @@ -78,11 +78,19 @@ def base_conversation_features(conversation_data, day_segment, requested_feature conversation_features["conversation_" + day_segment + "_maxconversationduration"] = conversation_data.groupby(["local_date"])['conv_Dur'].max() if "timefirstconversation" in features_to_compute: - conversation_features["conversation_" + day_segment + "_timefirstconversation"] = conversation_data[conversation_data["double_convo_start"]> 0].groupby(["local_date"])['double_convo_start'].min() + timeFirstConversation = conversation_data[conversation_data["double_convo_start"]> 0].groupby(["local_date"])[['double_convo_start','local_hour','local_minute']].min() + if 'local_hour' in timeFirstConversation.columns: + conversation_features["conversation_" + day_segment + "_timefirstconversation"] = timeFirstConversation["local_hour"]*60 + timeFirstConversation["local_minute"] + else: + conversation_features["conversation_" + day_segment + "_timefirstconversation"] = 0 if "timelastconversation" in features_to_compute: - conversation_features["conversation_" + day_segment + "_timelastconversation"] = conversation_data.groupby(["local_date"])['double_convo_start'].max() - + timeLastConversation = conversation_data[conversation_data["double_convo_start"] > 0].groupby(["local_date"])[['double_convo_start','local_hour','local_minute']].max() + if 'local_hour' in timeLastConversation: + conversation_features["conversation_" + day_segment + "_timelastconversation"] = timeLastConversation["local_hour"]*60 + timeLastConversation["local_minute"] + else: + conversation_features["conversation_" + day_segment + "_timelastconversation"] = 0 + if "sumenergy" in features_to_compute: conversation_features["conversation_" + day_segment + "_sumenergy"] = conversation_data.groupby(["local_date"])['double_energy'].sum()