Added count of unique 7-tuples and genus-species pairs.

notebooks/ToL_catalog_EDA.ipynb

@@ -499,6 +499,127 @@
     "We're at 8.4M+ entries with full taxonomic labels, so that's really good, especially considering 1,043,863 of the BIOSCAN sourced images don't have species labels."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "How about number of unique 7-tuples?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#number of unique 7-tuples in full dataset\n",
+    "df['duplicate'] = df.duplicated(subset = taxa, keep = 'first')\n",
+    "df_unique_taxa = df.loc[~df['duplicate']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Index: 454103 entries, 956203 to 11000902\n",
+      "Data columns (total 19 columns):\n",
+      " #   Column            Non-Null Count   Dtype  \n",
+      "---  ------            --------------   -----  \n",
+      " 0   split             454103 non-null  object \n",
+      " 1   treeoflife_id     454103 non-null  object \n",
+      " 2   eol_content_id    446988 non-null  float64\n",
+      " 3   eol_page_id       446988 non-null  float64\n",
+      " 4   bioscan_part      5328 non-null    float64\n",
+      " 5   bioscan_filename  5328 non-null    object \n",
+      " 6   inat21_filename   1787 non-null    object \n",
+      " 7   inat21_cls_name   1787 non-null    object \n",
+      " 8   inat21_cls_num    1787 non-null    float64\n",
+      " 9   kingdom           424949 non-null  object \n",
+      " 10  phylum            425412 non-null  object \n",
+      " 11  class             424296 non-null  object \n",
+      " 12  order             424642 non-null  object \n",
+      " 13  family            424513 non-null  object \n",
+      " 14  genus             427476 non-null  object \n",
+      " 15  species           414061 non-null  object \n",
+      " 16  common            454103 non-null  object \n",
+      " 17  data_source       454103 non-null  object \n",
+      " 18  duplicate         454103 non-null  bool   \n",
+      "dtypes: bool(1), float64(4), object(14)\n",
+      "memory usage: 66.3+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_unique_taxa.info(show_counts = True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "And number of unique `genus-species` pairs?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#number of unique genus-species pairs in full dataset\n",
+    "df['sciName-duplicate'] = df.duplicated(subset = ['genus', 'species'], keep = 'first')\n",
+    "df_unique_sciName = df.loc[~df['sciName-duplicate']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Index: 447462 entries, 956203 to 11000902\n",
+      "Data columns (total 20 columns):\n",
+      " #   Column             Non-Null Count   Dtype  \n",
+      "---  ------             --------------   -----  \n",
+      " 0   split              447462 non-null  object \n",
+      " 1   treeoflife_id      447462 non-null  object \n",
+      " 2   eol_content_id     441554 non-null  float64\n",
+      " 3   eol_page_id        441554 non-null  float64\n",
+      " 4   bioscan_part       5085 non-null    float64\n",
+      " 5   bioscan_filename   5085 non-null    object \n",
+      " 6   inat21_filename    823 non-null     object \n",
+      " 7   inat21_cls_name    823 non-null     object \n",
+      " 8   inat21_cls_num     823 non-null     float64\n",
+      " 9   kingdom            418488 non-null  object \n",
+      " 10  phylum             418888 non-null  object \n",
+      " 11  class              417965 non-null  object \n",
+      " 12  order              418287 non-null  object \n",
+      " 13  family             418677 non-null  object \n",
+      " 14  genus              425770 non-null  object \n",
+      " 15  species            412555 non-null  object \n",
+      " 16  common             447462 non-null  object \n",
+      " 17  data_source        447462 non-null  object \n",
+      " 18  duplicate          447462 non-null  bool   \n",
+      " 19  sciName-duplicate  447462 non-null  bool   \n",
+      "dtypes: bool(2), float64(4), object(14)\n",
+      "memory usage: 65.7+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_unique_sciName.info(show_counts = True)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

notebooks/ToL_catalog_EDA.py

@@ -85,6 +85,28 @@ df_all_taxa[taxa].info(show_counts = True)
 #
 # We're at 8.4M+ entries with full taxonomic labels, so that's really good, especially considering 1,043,863 of the BIOSCAN sourced images don't have species labels.
 
+# %% [markdown]
+# How about number of unique 7-tuples?
+
+# %%
+#number of unique 7-tuples in full dataset
+df['duplicate'] = df.duplicated(subset = taxa, keep = 'first')
+df_unique_taxa = df.loc[~df['duplicate']]
+
+# %%
+df_unique_taxa.info(show_counts = True)
+
+# %% [markdown]
+# And number of unique `genus-species` pairs?
+
+# %%
+#number of unique genus-species pairs in full dataset
+df['sciName-duplicate'] = df.duplicated(subset = ['genus', 'species'], keep = 'first')
+df_unique_sciName = df.loc[~df['sciName-duplicate']]
+
+# %%
+df_unique_sciName.info(show_counts = True)
+
 # %% [markdown]
 # More detail on these missing values from [`check_taxa` script](https://github.com/Imageomics/open_clip/blob/main/scripts/evobio10m/check_taxa.py) are displayed below. Note: full record of taxa check output is in `data/missing_taxa_output.txt`.
 #