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stress_at_work_analysis
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Compile a list of contact features and add a test.

communication
junos 2021-08-18 15:35:42 +02:00
parent c88336481e
commit 2d78aacd18
2 changed files with 34 additions and 35 deletions
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64
features/communication.py
View File

@ -37,6 +37,14 @@ FEATURES_SMS = (
# "no_received_ratio", "no_sent_ratio",
# "no_contacts"]
FEATURES_CONTACT = [
"proportion_calls_all",
"proportion_calls_incoming",
"proportion_calls_outgoing",
"proportion_calls_contacts",
"proportion_calls_missed_sms_received",
]
def get_call_data(usernames: Collection) -> pd.DataFrame:
"""
@ -287,38 +295,26 @@ def calls_sms_features(df_calls: pd.DataFrame, df_sms: pd.DataFrame) -> pd.DataF
"""
count_calls = count_comms(df_calls)
count_sms = count_comms(df_sms)
count_joined = (
count_calls.merge(
count_sms, on="participant_id", suffixes=("_calls", "_sms")
) # Merge calls and sms features
.reset_index() # Make participant_id a regular column
.assign(
proportion_calls=(
lambda x: x.no_calls_all / (x.no_calls_all + x.no_sms_all)
),
proportion_calls_incoming=(
lambda x: x.no_incoming / (x.no_incoming + x.no_received)
),
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)
),
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",
"proportion_calls",
"proportion_calls_incoming",
"proportion_calls_outgoing",
"proportion_calls_contacts",
"proportion_calls_missed_sms_received",
]
] # Filter out only the relevant features
)
count_joined = count_calls.merge(
count_sms, on="participant_id", suffixes=("_calls", "_sms")
).assign( # Merge calls and sms features
proportion_calls_all=(
lambda x: x.no_calls_all / (x.no_calls_all + x.no_sms_all)
),
proportion_calls_incoming=(
lambda x: x.no_incoming / (x.no_incoming + x.no_received)
),
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)
),
proportion_calls_contacts=(
lambda x: x.no_contacts_calls / (x.no_contacts_calls + x.no_contacts_sms)
)
# Calculate new features and create additional columns
)[
FEATURES_CONTACT
] # Filter out only the relevant features
return count_joined

5
test/test_communication.py
View File

@ -86,5 +86,8 @@ class CallsFeatures(unittest.TestCase):
def test_calls_sms_features(self):
self.features_call_sms = calls_sms_features(self.calls, self.sms)
print(self.features_call_sms.columns)
print(self.features_call_sms)
self.assertIsInstance(self.features_call_sms, pd.DataFrame)
self.assertCountEqual(
self.features_call_sms.columns.to_list(), FEATURES_CONTACT
)