chore(code): Move dataframe generation to module

src/process/generate_dataframes.py

@@ -0,0 +1,57 @@
+from pathlib import Path
+import re
+import seaborn as sns
+import src.globals as g
+
+## Creates 3 important data structures:
+# df: The main dataframe containing all final sample studies
+# df_by_intervention: The same dataframe but split up by individual interventions per study
+# validities: The studies with their validities, containing only quasi-/experimental studies
+
+from src.process import add_metadata as meta
+
+# raw database-search results
+bib_sample_raw_db = meta.bib_library_from_dir(g.RAW_DATA)
+# the complete library of sampled (and working) literature
+bib_sample = meta.bib_library_from_dir(g.WORKING_DATA)
+
+# load relevant studies
+from src.extract import load_data as load
+
+# each observation in a single dataframe
+df = meta.observations_with_metadata_df(
+    raw_observations = load.from_yml(g.PROCESSED_DATA),
+    study_metadata = meta.bib_metadata_df(bib_sample),
+    country_groups = meta.country_groups_df(Path(f"{g.SUPPLEMENTARY_DATA}/wb-country-groupings.xlsx")),
+)
+
+# all observations but split per individual intervention
+df_by_intervention = (
+    df
+    .fillna("")
+    .groupby(["author", "year", "title", "design", "method", "representativeness", "citation"])
+    .agg(
+        {
+            "intervention": lambda _col: "; ".join(_col),
+        }
+    )
+    .reset_index()
+    .drop_duplicates()
+    .assign(
+        intervention=lambda _df: _df["intervention"].apply(
+            lambda _cell: set([x.strip() for x in re.sub(r"\(.*\)", "", _cell).split(";")])
+        ),
+    )
+    .explode("intervention")
+)
+
+# Calc study validities (internal & external separated)
+from src.model import validity
+
+validities = validity.calculate(df_by_intervention)
+validities["identifier"] = validities["author"].str.replace(r',.*$', '', regex=True) + " (" + validities["year"].astype(str) + ")"
+validities = validities.loc[(validities["design"] == "quasi-experimental") | (validities["design"] == "experimental")]
+#validities["external_validity"] = validities["external_validity"].astype('category')
+validities["internal_validity"] = validities["internal_validity"].astype('category')
+validities["External Validity"] = validities["external_validity"]
+validities["Internal Validity"] = validities["internal_validity"]