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Reformat.

labels
junos 2022-03-15 13:28:51 +01:00
parent d470eef27e
commit 5f293211a7
1 changed files with 14 additions and 16 deletions
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30
src/features/phone_esm/straw/preprocess.py
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@ -1,21 +1,21 @@
import json import json
import numpy as np import numpy as np
import pandas as pd import pandas as pd
ESM_TYPE = { ESM_TYPE = {
"text": 1, "text": 1,
"radio": 2, "radio": 2,
"checkbox": 3, "checkbox": 3,
"likert": 4, "likert": 4,
"quick_answers": 5, "quick_answers": 5,
"scale": 6, "scale": 6,
"datetime": 7, "datetime": 7,
"pam": 8, "pam": 8,
"number": 9, "number": 9,
"web": 10, "web": 10,
"date": 11, "date": 11,
} }
ESM_STATUS_ANSWERED = 2 ESM_STATUS_ANSWERED = 2
@ -101,7 +101,7 @@ def clean_up_esm(df_esm_preprocessed: pd.DataFrame) -> pd.DataFrame:
df_esm = pd.read_csv(snakemake.input[0]) df_esm = pd.read_csv(snakemake.input[0])
df_esm_preprocessed = preprocess_esm(df_esm) df_esm_preprocessed = preprocess_esm(df_esm)
#TODO Enable getting the right questionnaire here. # TODO Enable getting the right questionnaire here.
df_esm_PANAS = df_esm_preprocessed[ df_esm_PANAS = df_esm_preprocessed[
(df_esm_preprocessed["questionnaire_id"] == 8) (df_esm_preprocessed["questionnaire_id"] == 8)
| (df_esm_preprocessed["questionnaire_id"] == 9) | (df_esm_preprocessed["questionnaire_id"] == 9)
@ -109,5 +109,3 @@ df_esm_PANAS = df_esm_preprocessed[
df_esm_clean = clean_up_esm(df_esm_PANAS) df_esm_clean = clean_up_esm(df_esm_PANAS)
df_esm_clean.to_csv(snakemake.output[0]) df_esm_clean.to_csv(snakemake.output[0])