Explore baseline screening data in a notebook.
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# ---
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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 datetime
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import seaborn as sns
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import pandas as pd
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nb_dir = os.path.split(os.getcwd())[0]
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if nb_dir not in sys.path: sys.path.append(nb_dir)
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import participants.query_db
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# %%
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baseline_si = pd.read_csv('E:/STRAWbaseline/results-survey637813.csv')
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baseline_be = pd.read_csv('E:/STRAWbaseline/results-survey358134.csv')
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# %%
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participants_inactive_usernames = participants.query_db.get_usernames(collection_start=datetime.date.fromisoformat("2020-08-01"))
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# %%
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baseline = pd.concat([baseline_si, baseline_be], join="inner").reset_index().drop(columns="index")
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baseline_inactive = baseline[baseline["Gebruikersnaam"].isin(participants_inactive_usernames)]
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# %%
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baseline
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# %%
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participants_inactive_usernames = pd.Series(participants.query_db.get_usernames(collection_start=datetime.date.fromisoformat("2020-08-01")))
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# %% [markdown]
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# # Demographic information
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# %% [markdown]
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# ## Numerus
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# %%
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print(baseline_inactive.shape[0])
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print(participants_inactive_usernames.shape[0])
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# %%
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participants_inactive_usernames[~participants_inactive_usernames.isin(baseline["Gebruikersnaam"])].sort_values()
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# %%
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baseline_inactive["startlanguage"].value_counts()
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# %%
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baseline_inactive["Geslacht"].value_counts()
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# %%
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now = pd.Timestamp('now')
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baseline_inactive = baseline_inactive.assign(dob = lambda x: pd.to_datetime(x.Geboortedatum),
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age = lambda x: now - x.dob)
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# %%
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baseline_inactive["age"].describe()
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# %%
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3710/365.25
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# %%
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