76 lines
2.7 KiB
Python
76 lines
2.7 KiB
Python
import pandas as pd
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pid = snakemake.params["pid"]
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requested_features = snakemake.params["features"]
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baseline_features = pd.DataFrame(columns=requested_features)
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question_filename = snakemake.params["question_filename"]
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JCQ_DEMAND = "JobEisen"
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JCQ_CONTROL = "JobControle"
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dict_JCQ_demand_control_reverse = {
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JCQ_DEMAND: {
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3: " [Od mene se ne zahteva,",
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4: " [Imam dovolj časa, da končam",
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5: " [Pri svojem delu se ne srečujem s konfliktnimi",
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},
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JCQ_CONTROL: {
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2: " |Moje delo vključuje veliko ponavljajočega",
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6: " [Pri svojem delu imam zelo malo svobode",
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},
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}
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LIMESURVEY_JCQ_MIN = 1
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LIMESURVEY_JCQ_MAX = 4
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participant_info = pd.read_csv(snakemake.input[0], parse_dates=["date_of_birth"])
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if not participant_info.empty:
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if "age" in requested_features:
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now = pd.Timestamp("now")
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baseline_features.loc[0, "age"] = (
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now - participant_info.loc[0, "date_of_birth"]
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).days / 365.25245
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if "gender" in requested_features:
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baseline_features.loc[0, "gender"] = participant_info.loc[0, "gender"]
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if "startlanguage" in requested_features:
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baseline_features.loc[0, "startlanguage"] = participant_info.loc[
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0, "startlanguage"
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]
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if "demand" in requested_features:
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participant_info_t = participant_info.T
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rows_baseline = participant_info_t.index
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# Find questions about demand, but disregard time (duration of filling in questionnaire)
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rows_demand = rows_baseline.str.startswith(
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JCQ_DEMAND
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) & ~rows_baseline.str.endswith("Time")
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limesurvey_control = (
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participant_info_t[rows_demand]
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.reset_index()
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.rename(columns={"index": "question", 0: "score_original"})
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)
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# Extract question IDs from names such as JobEisen[3]
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limesurvey_control.loc[:, "qid"] = (
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limesurvey_control["question"].str.extract(r"\[(\d+)\]").astype(int)
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)
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limesurvey_control["score"] = limesurvey_control["score_original"]
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# Identify rows that include questions to be reversed.
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rows_demand_reverse = limesurvey_control["qid"].isin(
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dict_JCQ_demand_control_reverse[JCQ_DEMAND].keys()
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)
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# Reverse the score, so that the maximum value becomes the minimum etc.
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limesurvey_control.loc[rows_demand_reverse, "score"] = (
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LIMESURVEY_JCQ_MAX
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+ LIMESURVEY_JCQ_MIN
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- limesurvey_control.loc[rows_demand_reverse, "score_original"]
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)
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# TODO Write to data/interim
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baseline_features.loc[0, "limesurvey_demand"] = limesurvey_control[
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"score"
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].sum()
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baseline_features.to_csv(
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snakemake.output[0], index=False, encoding="utf-8",
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)
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