127 lines
2.4 KiB
Python
127 lines
2.4 KiB
Python
# ---
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# jupyter:
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# jupytext:
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# formats: ipynb,py:percent
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# text_representation:
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# extension: .py
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# format_name: percent
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# format_version: '1.3'
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# jupytext_version: 1.11.2
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# kernelspec:
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# display_name: straw2analysis
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# language: python
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# name: straw2analysis
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# ---
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# %%
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import os
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import sys
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import matplotlib.pyplot as plt
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# %%
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import seaborn as sns
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nb_dir = os.path.split(os.getcwd())[0]
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if nb_dir not in sys.path:
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sys.path.append(nb_dir)
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# %%
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from features.communication import *
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# %% [markdown]
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# # Example of communication data and feature calculation
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# %%
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df_calls = get_call_data(["nokia_0000003"])
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print(df_calls)
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# %%
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count_comms(df_calls)
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# %%
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df_sms = get_sms_data(["nokia_0000003"])
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count_comms(df_sms)
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# %% [markdown]
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# # Call data
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# %%
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import participants.query_db
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# %%
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participants_inactive_usernames = participants.query_db.get_usernames()
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df_calls_inactive = get_call_data(participants_inactive_usernames)
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# %%
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df_calls_features = count_comms(df_calls_inactive)
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df_calls_features.head()
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# %%
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df_calls_features.describe()
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# %%
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calls_number = pd.wide_to_long(
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df_calls_features.reset_index(),
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i="participant_id",
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j="call_type",
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stubnames="no",
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sep="_",
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suffix="\D+",
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)
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# %%
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sns.displot(calls_number, x="no", hue="call_type", binwidth=5, element="step", height=8)
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# %%
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calls_duration = pd.wide_to_long(
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df_calls_features.reset_index(),
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i="participant_id",
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j="call_type",
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stubnames="duration",
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sep="_",
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suffix="\D+",
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)
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sns.displot(
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calls_duration,
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x="duration",
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hue="call_type",
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multiple="dodge",
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height=8,
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log_scale=(True, False),
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)
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# %% [markdown]
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# ## Most frequent contacts by participant
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# %%
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df_calls_inactive = enumerate_contacts(df_calls_inactive)
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df_calls_inactive.tail()
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# %%
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df_calls_frequent = df_calls_inactive.query("contact_id < 5")
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# %%
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sns.boxplot(x="contact_id", y="freq", data=df_calls_frequent)
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# %% [markdown]
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# # SMS data
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# %%
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df_sms_inactive = get_sms_data(participants_inactive_usernames)
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df_sms_features = count_comms(df_sms_inactive)
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df_sms_features.describe()
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# %%
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sms_number = pd.wide_to_long(
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df_sms_features.reset_index(),
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i="participant_id",
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j="message_type",
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stubnames="no",
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sep="_",
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suffix="\D+",
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)
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sns.displot(
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sms_number, x="no", hue="message_type", binwidth=5, element="step", height=8
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)
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