218 lines
4.5 KiB
Python
218 lines
4.5 KiB
Python
# ---
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# jupyter:
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# jupytext:
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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: 1.14.5
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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 pandas as pd
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from features.esm_JCQ import dict_JCQ_demand_control_reverse
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# %%
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limesurvey_questions = pd.read_csv(
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"E:/STRAWbaseline/survey637813+question_text.csv", header=None
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).T
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# %%
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limesurvey_questions
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# %%
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limesurvey_questions[["code", "text"]] = limesurvey_questions[0].str.split(
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r"\.\s", expand=True, n=1
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)
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# %%
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limesurvey_questions
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# %%
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demand_reverse_lime_rows = (
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limesurvey_questions["text"].str.startswith(" [Od mene se ne zahteva,")
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| limesurvey_questions["text"].str.startswith(" [Imam dovolj časa, da končam")
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| limesurvey_questions["text"].str.startswith(
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" [Pri svojem delu se ne srečujem s konfliktnimi"
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)
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)
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control_reverse_lime_rows = limesurvey_questions["text"].str.startswith(
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" [Moje delo vključuje veliko ponavljajočega"
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) | limesurvey_questions["text"].str.startswith(
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" [Pri svojem delu imam zelo malo svobode"
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)
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# %%
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demand_reverse_lime = limesurvey_questions[demand_reverse_lime_rows]
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demand_reverse_lime.loc[:, "qid"] = demand_reverse_lime["code"].str.extract(
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r"\[(\d+)\]"
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)
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control_reverse_lime = limesurvey_questions[control_reverse_lime_rows]
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control_reverse_lime.loc[:, "qid"] = control_reverse_lime["code"].str.extract(
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r"\[(\d+)\]"
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)
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# %%
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limesurvey_questions.loc[89, "text"]
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# %%
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limesurvey_questions[limesurvey_questions["code"].str.startswith("JobEisen")]
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# %%
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demand_reverse_lime
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# %%
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control_reverse_lime
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# %%
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participant_info = pd.read_csv(
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"C:/Users/junos/Documents/FWO-ARRS/Analysis/straw2analysis/rapids/data/raw/p031/participant_baseline_raw.csv",
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parse_dates=["date_of_birth"],
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)
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# %%
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participant_info_t = participant_info.T
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# %%
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rows_baseline = participant_info_t.index
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# %%
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rows_demand = rows_baseline.str.startswith("JobEisen") & ~rows_baseline.str.endswith(
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"Time"
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)
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# %%
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rows_baseline[rows_demand]
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# %%
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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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# %%
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limesurvey_control
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# %%
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limesurvey_control["qid"] = (
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limesurvey_control["question"].str.extract(r"\[(\d+)\]").astype(int)
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)
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# %%
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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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# %%
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limesurvey_control["qid"][0]
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# %%
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rows_demand_reverse = limesurvey_control["qid"].isin(
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dict_JCQ_demand_control_reverse.keys()
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)
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limesurvey_control.loc[rows_demand_reverse, "score"] = (
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4 + 1 - limesurvey_control.loc[rows_demand_reverse, "score_original"]
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)
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# %%
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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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# %%
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limesurvey_control
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# %%
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test = pd.DataFrame(
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data={"question": "one", "score_original": 3, "score": 3, "qid": 10}, index=[0]
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)
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# %%
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pd.concat([test, limesurvey_control]).reset_index()
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# %%
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limesurvey_control["score"].sum()
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# %%
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rows_demand_reverse
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# %%
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dict_JCQ_demand_control_reverse[JCQ_DEMAND].keys()
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# %%
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limesurvey_control
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# %%
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DEMAND_CONTROL_RATIO_MIN = 5 / (9 * 4)
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DEMAND_CONTROL_RATIO_MAX = (4 * 5) / 9
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JCQ_NORMS = {
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"F": {
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0: DEMAND_CONTROL_RATIO_MIN,
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1: 0.45,
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2: 0.52,
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3: 0.62,
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4: DEMAND_CONTROL_RATIO_MAX,
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},
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"M": {
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0: DEMAND_CONTROL_RATIO_MIN,
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1: 0.41,
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2: 0.48,
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3: 0.56,
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4: DEMAND_CONTROL_RATIO_MAX,
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},
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}
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# %%
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JCQ_NORMS[participant_info.loc[0, "gender"]][0]
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# %%
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participant_info_t.index.str.startswith("JobControle")
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# %%
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columns_baseline = participant_info.columns
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# %%
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columns_demand = columns_baseline.str.startswith(
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"JobControle"
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) & ~columns_baseline.str.endswith("Time")
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# %%
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columns_baseline[columns_demand]
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# %%
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participant_control = participant_info.loc[:, columns_demand]
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# %%
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participant_control["id"] = participant_control.index
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# %%
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participant_control
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# %%
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pd.wide_to_long(
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participant_control,
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stubnames="JobControle",
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i="id",
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j="qid",
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sep="[",
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suffix="(\\d+)]",
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)
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