42 lines
2.1 KiB
Python
42 lines
2.1 KiB
Python
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"""
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This script can create the multiple timezones file based on timezone table collected by the AWARE app.
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Input: timezone table collected by the AWARE app
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---
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Expected output:
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| Column | Description |
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|-------------|---------------------------------------------------------------------------------------------------------------|
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| device_id | A string that uniquely identifies a smartphone or wearable |
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| tzcode | A string with the appropriate code from this list that represents the time zone where the device sensed data |
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| timestamp | A UNIX timestamp indicating when was the first time this device_id sensed data in tzcode |
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How to run it?
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1. Put the timezone table (timezone.csv) collected by the AWARE app under data/external folder
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2. Run python tools/create_multi_timezones_file.py
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"""
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import re
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import pandas as pd
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# Load the timezone table collected by the AWARE app
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data = pd.read_csv("data/external/timezone.csv")
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# Load the first table of the List of tz database time zones page in wiki (Link: https://en.wikipedia.org/wiki/List_of_tz_database_time_zones)
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wiki_tz = pd.read_csv("data/external/wiki_tz.csv")
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data["tzcode"] = data["timezone"].str.extract("("+"|".join(wiki_tz["TZ database name"].tolist())+")", expand=False)
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data = data[["device_id", "tzcode", "timestamp"]]
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# Sort by device_id and timestamp
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data.sort_values(by=["device_id", "timestamp"], inplace=True)
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# Only keep the first & last row for consecutive rows with the same tzcode per device_id
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data_first = data.loc[(data["device_id"].shift(1) != data["device_id"]) | (data["tzcode"].shift(1) != data["tzcode"])]
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data_last = data.loc[(data["device_id"].shift(-1) != data["device_id"]) | (data["tzcode"].shift(-1) != data["tzcode"])]
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data = pd.concat([data_first, data_last], axis=0)
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# Drop duplicates and sort by device_id and timestamp
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data = data.drop_duplicates()
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data.sort_values(by=["device_id", "timestamp"], inplace=True)
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data.to_csv("data/external/multiple_timezones.csv", index=False)
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