🐛 add dependencies specific to notebook

- pandas 2.0 requires numeric values for mean aggregation
RasmussenLab · Oct 30, 2023 · fbc8164 · fbc8164
1 parent cf32a42
commit fbc8164
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Showing 2 changed files with 15 additions and 2 deletions.
diff --git a/tutorial/log_reg.ipynb b/tutorial/log_reg.ipynb
@@ -14,6 +14,16 @@
     "> Predict Alzheimer disease based on proteomics measurements."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cd90b1b6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install njab heatmapz openpyxl "
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -672,7 +682,7 @@
     "    return_train_score=True,\n",
     "    # fit_params=dict(sample_weight=weights)\n",
     ")\n",
-    "cv_feat = cv_feat.groupby('n_features').agg(['mean', 'std'])\n",
+    "cv_feat = cv_feat.drop('test_case', axis=1).groupby('n_features').agg(['mean', 'std'])\n",
     "cv_feat"
    ]
   },

diff --git a/tutorial/log_reg.py b/tutorial/log_reg.py
@@ -22,6 +22,9 @@
 #
 # > Predict Alzheimer disease based on proteomics measurements.
 
+# %%
+# !pip install njab heatmapz openpyxl 
+
 # %%
 import itertools
 import logging
@@ -366,7 +369,7 @@
     return_train_score=True,
     # fit_params=dict(sample_weight=weights)
 )
-cv_feat = cv_feat.groupby('n_features').agg(['mean', 'std'])
+cv_feat = cv_feat.drop('test_case', axis=1).groupby('n_features').agg(['mean', 'std'])
 cv_feat
 
 # %% [markdown]