stress_at_work_analysis/exploration/test_JCQ_reversal.py

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# ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: percent
# format_version: '1.3'
# jupytext_version: 1.14.5
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# display_name: straw2analysis
# language: python
# name: straw2analysis
# ---
# %%
import pandas as pd
from features.esm_JCQ import dict_JCQ_demand_control_reverse
# %%
limesurvey_questions = pd.read_csv(
"E:/STRAWbaseline/survey637813+question_text.csv", header=None
).T
# %%
limesurvey_questions
# %%
limesurvey_questions[["code", "text"]] = limesurvey_questions[0].str.split(
r"\.\s", expand=True, n=1
)
# %%
limesurvey_questions
# %%
demand_reverse_lime_rows = (
limesurvey_questions["text"].str.startswith(" [Od mene se ne zahteva,")
| limesurvey_questions["text"].str.startswith(" [Imam dovolj časa, da končam")
| limesurvey_questions["text"].str.startswith(
" [Pri svojem delu se ne srečujem s konfliktnimi"
)
)
control_reverse_lime_rows = limesurvey_questions["text"].str.startswith(
" [Moje delo vključuje veliko ponavljajočega"
) | limesurvey_questions["text"].str.startswith(
" [Pri svojem delu imam zelo malo svobode"
)
# %%
demand_reverse_lime = limesurvey_questions[demand_reverse_lime_rows]
demand_reverse_lime.loc[:, "qid"] = demand_reverse_lime["code"].str.extract(
r"\[(\d+)\]"
)
control_reverse_lime = limesurvey_questions[control_reverse_lime_rows]
control_reverse_lime.loc[:, "qid"] = control_reverse_lime["code"].str.extract(
r"\[(\d+)\]"
)
# %%
limesurvey_questions.loc[89, "text"]
# %%
limesurvey_questions[limesurvey_questions["code"].str.startswith("JobEisen")]
# %%
demand_reverse_lime
# %%
control_reverse_lime
# %%
participant_info = pd.read_csv(
"C:/Users/junos/Documents/FWO-ARRS/Analysis/straw2analysis/rapids/data/raw/p031/participant_baseline_raw.csv",
parse_dates=["date_of_birth"],
)
# %%
participant_info_t = participant_info.T
# %%
rows_baseline = participant_info_t.index
# %%
rows_demand = rows_baseline.str.startswith("JobEisen") & ~rows_baseline.str.endswith(
"Time"
)
# %%
rows_baseline[rows_demand]
# %%
limesurvey_control = (
participant_info_t[rows_demand]
.reset_index()
.rename(columns={"index": "question", 0: "score_original"})
)
# %%
limesurvey_control
# %%
limesurvey_control["qid"] = (
limesurvey_control["question"].str.extract(r"\[(\d+)\]").astype(int)
)
# %%
limesurvey_control["question"].str.extract(r"\[(\d+)\]").astype(int)
# %%
limesurvey_control["score"] = limesurvey_control["score_original"]
# %%
limesurvey_control["qid"][0]
# %%
rows_demand_reverse = limesurvey_control["qid"].isin(
dict_JCQ_demand_control_reverse.keys()
)
limesurvey_control.loc[rows_demand_reverse, "score"] = (
4 + 1 - limesurvey_control.loc[rows_demand_reverse, "score_original"]
)
# %%
JCQ_DEMAND = "JobEisen"
JCQ_CONTROL = "JobControle"
dict_JCQ_demand_control_reverse = {
JCQ_DEMAND: {
3: " [Od mene se ne zahteva,",
4: " [Imam dovolj časa, da končam",
5: " [Pri svojem delu se ne srečujem s konfliktnimi",
},
JCQ_CONTROL: {
2: " |Moje delo vključuje veliko ponavljajočega",
6: " [Pri svojem delu imam zelo malo svobode",
},
}
# %%
limesurvey_control
# %%
test = pd.DataFrame(
data={"question": "one", "score_original": 3, "score": 3, "qid": 10}, index=[0]
)
# %%
pd.concat([test, limesurvey_control]).reset_index()
# %%
limesurvey_control["score"].sum()
# %%
rows_demand_reverse
# %%
dict_JCQ_demand_control_reverse[JCQ_DEMAND].keys()
# %%
limesurvey_control
# %%
DEMAND_CONTROL_RATIO_MIN = 5 / (9 * 4)
DEMAND_CONTROL_RATIO_MAX = (4 * 5) / 9
JCQ_NORMS = {
"F": {
0: DEMAND_CONTROL_RATIO_MIN,
1: 0.45,
2: 0.52,
3: 0.62,
4: DEMAND_CONTROL_RATIO_MAX,
},
"M": {
0: DEMAND_CONTROL_RATIO_MIN,
1: 0.41,
2: 0.48,
3: 0.56,
4: DEMAND_CONTROL_RATIO_MAX,
},
}
# %%
JCQ_NORMS[participant_info.loc[0, "gender"]][0]
# %%
participant_info_t.index.str.startswith("JobControle")
# %%
columns_baseline = participant_info.columns
# %%
columns_demand = columns_baseline.str.startswith(
"JobControle"
) & ~columns_baseline.str.endswith("Time")
# %%
columns_baseline[columns_demand]
# %%
participant_control = participant_info.loc[:, columns_demand]
# %%
participant_control["id"] = participant_control.index
# %%
participant_control
# %%
pd.wide_to_long(
participant_control,
stubnames="JobControle",
i="id",
j="qid",
sep="[",
suffix="(\\d+)]",
)