Calculate JCQ demand score.

Hardcode question IDs to be reversed.
labels
junos 2022-02-28 18:30:41 +01:00
parent 30ac8b1cd5
commit 2fed962644
1 changed files with 47 additions and 10 deletions

View File

@ -5,13 +5,26 @@ requested_features = snakemake.params["features"]
baseline_features = pd.DataFrame(columns=requested_features) baseline_features = pd.DataFrame(columns=requested_features)
question_filename = snakemake.params["question_filename"] question_filename = snakemake.params["question_filename"]
JCQ_DEMAND = "JobEisen"
JCQ_CONTROL = "JobControle"
dict_JCQ_demand_control_reverse = { dict_JCQ_demand_control_reverse = {
"demand_0": " [Od mene se ne zahteva,", JCQ_DEMAND: {
"demand_1": " [Imam dovolj časa, da končam", 3: " [Od mene se ne zahteva,",
"demand_2": " [Pri svojem delu se ne srečujem s konfliktnimi" 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_JCQ_MIN = 1
LIMESURVEY_JCQ_MAX = 4
participant_info = pd.read_csv(snakemake.input[0], parse_dates=["date_of_birth"]) participant_info = pd.read_csv(snakemake.input[0], parse_dates=["date_of_birth"])
if not participant_info.empty: if not participant_info.empty:
if "age" in requested_features: if "age" in requested_features:
now = pd.Timestamp("now") now = pd.Timestamp("now")
@ -25,13 +38,37 @@ if not participant_info.empty:
0, "startlanguage" 0, "startlanguage"
] ]
if "demand" in requested_features: if "demand" in requested_features:
limesurvey_questions = pd.read_csv(question_filename, header=None).T participant_info_t = participant_info.T
limesurvey_questions[["code", "text"]] = limesurvey_questions[0].str.split(r"\.\s", expand=True, n=1) rows_baseline = participant_info_t.index
demand_reverse_lime_rows = limesurvey_questions["text"].str.startswith(dict_JCQ_demand_control_reverse["demand_0"]) | \ # Find questions about demand, but disregard time (duration of filling in questionnaire)
limesurvey_questions["text"].str.startswith(dict_JCQ_demand_control_reverse["demand_1"]) | \ rows_demand = rows_baseline.str.startswith(
limesurvey_questions["text"].str.startswith(dict_JCQ_demand_control_reverse["demand_2"]) JCQ_DEMAND
demand_reverse_lime = limesurvey_questions[demand_reverse_lime_rows] ) & ~rows_baseline.str.endswith("Time")
demand_reverse_lime.loc[:, "qid"] = demand_reverse_lime["code"].str.extract(r"\[(\d+)\]") limesurvey_control = (
participant_info_t[rows_demand]
.reset_index()
.rename(columns={"index": "question", 0: "score_original"})
)
# Extract question IDs from names such as JobEisen[3]
limesurvey_control.loc[:, "qid"] = (
limesurvey_control["question"].str.extract(r"\[(\d+)\]").astype(int)
)
limesurvey_control["score"] = limesurvey_control["score_original"]
# Identify rows that include questions to be reversed.
rows_demand_reverse = limesurvey_control["qid"].isin(
dict_JCQ_demand_control_reverse[JCQ_DEMAND].keys()
)
# Reverse the score, so that the maximum value becomes the minimum etc.
limesurvey_control.loc[rows_demand_reverse, "score"] = (
LIMESURVEY_JCQ_MAX
+ LIMESURVEY_JCQ_MIN
- limesurvey_control.loc[rows_demand_reverse, "score_original"]
)
# TODO Write to data/interim
baseline_features.loc[0, "limesurvey_demand"] = limesurvey_control[
"score"
].sum()
baseline_features.to_csv( baseline_features.to_csv(
snakemake.output[0], index=False, encoding="utf-8", snakemake.output[0], index=False, encoding="utf-8",