feat: add scripts to repo

scripts/convert-with-core.py

@@ -0,0 +1,82 @@
+from pathlib import Path
+
+import janitor.polars  # noqa: F401
+import polars as pl
+
+resource_dir = Path(__file__).resolve().parent.parent
+folder_path = resource_dir / "data-raw"
+
+df_experiment1 = pl.read_csv(folder_path / "Expe1.csv", infer_schema_length=100_000)
+
+df_experiment1 = df_experiment1.rename(
+    {
+        "bead_size": "bead_size_mm",
+        "burial_depth": "burial_depth_cm",
+        "cylinder": "cylinder_id",
+        "movedup": "num_beads_moved_up",
+        "moveddown": "num_beads_moved_down",
+        "nomoved": "num_beads_no_movement",
+        "total_beads": "total_num_beads",
+        "proportion_movedup": "proportion_beads_moved_up",
+        "proportion_moveddown": "proportion_beads_moved_down",
+        "proportion_nomoved": "proportion_beads_no_movement",
+    }
+)
+df_experiment1.write_csv(folder_path / "data-experiment1-ready.csv")
+
+df_experiment2 = pl.read_csv(folder_path / "Expe2.csv", infer_schema_length=100_000)
+
+treatment_mapping1 = {
+    "masHmasE": "with_feces_cover_after_48h",
+    "masHmenE": "with_feces_cover_after_0h",
+    "menHmenE": "without_feces_cover_after_0h",
+}
+
+df_experiment2 = (
+    df_experiment2.with_columns(pl.col("beetle_treatment").replace(treatment_mapping1))
+    .rename(
+        {
+            "site": "site_id",
+            "burial_depth": "burial_depth_cm",
+            "bottle": "bottle_id",
+            "plant_species": "plant_species_name",
+            "total_seeds": "total_num_seeds",
+            "emerged_seedlings": "num_emerged_seedlings",
+            "proportion": "proportion_emerged_seedlings",
+        }
+    )
+    .clean_names()
+)
+
+df_experiment2.write_csv(folder_path / "data-experiment2-ready.csv")
+
+df_abundance = pl.read_csv(
+    folder_path / "Expe3Abundance.csv", infer_schema_length=100_000
+)
+
+treatment_mapping2 = {
+    "masHmasE1": "feces_once_beetle_access",
+    "masHmenE1": "feces_once_beetle_exclusion",
+    "masHmasE4": "feces_four_beetle_access",
+    "masHmenE4": "feces_four_beetle_exclusion",
+    "menHmenE": "feces_exclusion_beetle_exclusion",
+}
+df_abundance = df_abundance.with_columns(
+    pl.col("beetle_treatment").replace(treatment_mapping2)
+)
+
+df_richness = pl.read_csv(
+    folder_path / "Expe3Richness.csv", infer_schema_length=100_000
+)
+
+df_experiment3_all = pl.concat([df_abundance, df_richness], how="align")  # concat wide
+
+df_experiment3_all = df_experiment3_all.rename(
+    {"time_measurement": "time_measurement_weeks", "site": "site_id", "plot": "plot_id"}
+)
+
+df_experiment3_all.write_csv(folder_path / "data-experiment3-ready.csv")
+
+df_experiment1.glimpse()
+df_experiment2.glimpse()
+df_experiment3_all.glimpse()

scripts/download-data.py

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+from pathlib import Path
+from zipfile import ZipFile
+
+import requests
+
+resource_dir = Path(__file__).resolve().parent.parent
+folder_path = resource_dir / "data-raw"
+
+# Download and save the zip file
+all_files = requests.get("https://zenodo.org/api/records/4965431/files-archive")
+
+all_files_path = folder_path / "all_files.zip"
+with open(all_files_path, "wb") as file:
+    file.write(all_files.content)
+
+# Extract the zip file
+with ZipFile(all_files_path, "r") as zip_ref:
+    zip_ref.extractall(folder_path)