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"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"TOL_FILEPATH = \"../../data/\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Read in Links CSV files\n",
"\n",
"Full cargo archives have some more content than the [original `links_inner` file](https://huggingface.co/datasets/imageomics/ToL-EDA/blob/fa08e0f6692a013e4e4f5ca30dd0e8883c0021d8/eol_realign/data/links_inner.csv) and the [original `links_manifest_cargo_on_md5.csv`](https://huggingface.co/datasets/imageomics/ToL-EDA/blob/fa08e0f6692a013e4e4f5ca30dd0e8883c0021d8/eol_realign/data/links_manifest_cargo_on_md5.csv).\n",
"\n",
"From Matt:\n",
"> It represents a series of inner merges:\n",
"> 1. The list of images in the EOL cargo archive (used to create the webdatasets) with the EOL portion of `catalog.csv`\n",
"> - Merged on a combined identifier of `eol_content_id` and `eol_page_id`.\n",
"> Result from 1) with the list of images redownloaded from all 3 media manifests we touched around the original download time (identified [here](https://huggingface.co/datasets/imageomics/ToL-EDA/discussions/5#6584808d92eba5ad69b8379f)).\n",
"> - Merged on MD5\n",
">\n",
"> The result has 6,219,674 unique `treeoflife_id` entries and 6,146,917 unique `md5` entries. It has the combined `eol_content_id` and `eol_page_id` identifiers used at each stage:\n",
"- `combined_id_catalog`: represents what's in the original catalog \n",
"- `combined_id_manifest_full_manifest`: represents what's in the combined manifest from all 3 dates \n",
"> It also has an indicator of which of the three media manifest files each entry was present in (one or more) in columns representing retreival date (eg., `source_0706`: indicates if it was present in the manifest retrieved on July 6, 2023). It also has the copyright owner and license information as contained in the media manifest files.\n",
">\n",
"> Still needs to be run through the owner name finding code. ([owner_match](https://huggingface.co/datasets/imageomics/ToL-EDA/blob/71ad5b49226a3a49634931005eeb340b3c96db13/scripts/match_owners.py) --note: this version uses inner merges, so will remove entries without media info. Probably should adjust this.)\n",
"\n",
"For reference on the numbers, there are 6,250,420 EOL images in TreeOfLife-10M (the catalog). Comparing with `links_inner` previously (from [`links_inner.csv`](https://huggingface.co/datasets/imageomics/ToL-EDA/blob/fa08e0f6692a013e4e4f5ca30dd0e8883c0021d8/eol_realign/data/links_inner.csv)) we were missing 31,376 images, 29 of which were identified in [`links_manifest_cargo_on_md5.csv`](https://huggingface.co/datasets/imageomics/ToL-EDA/blob/fa08e0f6692a013e4e4f5ca30dd0e8883c0021d8/eol_realign/data/links_manifest_cargo_on_md5.csv)."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"links_inner = pd.read_csv(\"../data/eol-cargo-archive_catalog_combined-manifest-checksums_links.csv\", low_memory=False)\n",
"links_manifest_cargo = pd.read_csv(\"../data/eol-cargo-archive_combined-manifest-checksums_links.csv\", low_memory=False)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 6841202 entries, 0 to 6841201\n",
"Data columns (total 30 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 filename_archive 6841202 non-null object \n",
" 1 md5 6841202 non-null object \n",
" 2 combined_id_archive 6841202 non-null object \n",
" 3 split 6841202 non-null object \n",
" 4 treeoflife_id 6841202 non-null object \n",
" 5 bioscan_part 0 non-null float64\n",
" 6 bioscan_filename 0 non-null float64\n",
" 7 inat21_filename 0 non-null float64\n",
" 8 inat21_cls_name 0 non-null float64\n",
" 9 inat21_cls_num 0 non-null float64\n",
" 10 kingdom 6551473 non-null object \n",
" 11 phylum 6553206 non-null object \n",
" 12 class 6532009 non-null object \n",
" 13 order 6525621 non-null object \n",
" 14 family 6506076 non-null object \n",
" 15 genus 6486130 non-null object \n",
" 16 species 6406307 non-null object \n",
" 17 common 6841202 non-null object \n",
" 18 combined_id_catalog 6841202 non-null object \n",
" 19 filename_manifest 6841202 non-null object \n",
" 20 combined_id_manifest_redownload 6841202 non-null object \n",
" 21 medium_source_url 6841202 non-null object \n",
" 22 eol_full_size_copy_url 6841202 non-null object \n",
" 23 license_name 6841202 non-null object \n",
" 24 copyright_owner 6208498 non-null object \n",
" 25 expected_image_filename 6841202 non-null object \n",
" 26 source_0706 6841202 non-null bool \n",
" 27 source_0726 6841202 non-null bool \n",
" 28 source_1206 6841202 non-null bool \n",
" 29 combined_id_full_manifest 6841202 non-null object \n",
"dtypes: bool(3), float64(5), object(22)\n",
"memory usage: 1.4+ GB\n"
]
}
],
"source": [
"links_inner.info(show_counts=True)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 7514001 entries, 0 to 7514000\n",
"Data columns (total 17 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 filename_archive 7514001 non-null object\n",
" 1 md5_archive 7514001 non-null object\n",
" 2 combined_id_archive 7514001 non-null object\n",
" 3 filename_manifest 7514001 non-null object\n",
" 4 md5_combined_manifest 7514001 non-null object\n",
" 5 combined_id_manifest_redownload 7514001 non-null object\n",
" 6 eol_content_id 7514001 non-null int64 \n",
" 7 eol_page_id 7514001 non-null int64 \n",
" 8 medium_source_url 7514001 non-null object\n",
" 9 eol_full_size_copy_url 7514001 non-null object\n",
" 10 license_name 7514001 non-null object\n",
" 11 copyright_owner 6860825 non-null object\n",
" 12 expected_image_filename 7514001 non-null object\n",
" 13 source_0706 7514001 non-null bool \n",
" 14 source_0726 7514001 non-null bool \n",
" 15 source_1206 7514001 non-null bool \n",
" 16 combined_id_full_manifest 7514001 non-null object\n",
"dtypes: bool(3), int64(2), object(12)\n",
"memory usage: 824.1+ MB\n"
]
}
],
"source": [
"links_manifest_cargo.info(show_counts=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These both have about 600-700 more entries than the earlier files."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>filename_archive</th>\n",
" <th>md5_archive</th>\n",
" <th>combined_id_archive</th>\n",
" <th>filename_manifest</th>\n",
" <th>md5_combined_manifest</th>\n",
" <th>combined_id_manifest_redownload</th>\n",
" <th>eol_content_id</th>\n",
" <th>eol_page_id</th>\n",
" <th>medium_source_url</th>\n",
" <th>eol_full_size_copy_url</th>\n",
" <th>license_name</th>\n",
" <th>copyright_owner</th>\n",
" <th>expected_image_filename</th>\n",
" <th>source_0706</th>\n",
" <th>source_0726</th>\n",
" <th>source_1206</th>\n",
" <th>combined_id_full_manifest</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"Empty DataFrame\n",
"Columns: [filename_archive, md5_archive, combined_id_archive, filename_manifest, md5_combined_manifest, combined_id_manifest_redownload, eol_content_id, eol_page_id, medium_source_url, eol_full_size_copy_url, license_name, copyright_owner, expected_image_filename, source_0706, source_0726, source_1206, combined_id_full_manifest]\n",
"Index: []"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# These should be the same\n",
"links_manifest_cargo.loc[links_manifest_cargo[\"combined_id_manifest_redownload\"] != links_manifest_cargo[\"combined_id_full_manifest\"]]"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 822558 entries, 2 to 7513999\n",
"Data columns (total 17 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 filename_archive 822558 non-null object\n",
" 1 md5_archive 822558 non-null object\n",
" 2 combined_id_archive 822558 non-null object\n",
" 3 filename_manifest 822558 non-null object\n",
" 4 md5_combined_manifest 822558 non-null object\n",
" 5 combined_id_manifest_redownload 822558 non-null object\n",
" 6 eol_content_id 822558 non-null int64 \n",
" 7 eol_page_id 822558 non-null int64 \n",
" 8 medium_source_url 822558 non-null object\n",
" 9 eol_full_size_copy_url 822558 non-null object\n",
" 10 license_name 822558 non-null object\n",
" 11 copyright_owner 797147 non-null object\n",
" 12 expected_image_filename 822558 non-null object\n",
" 13 source_0706 822558 non-null bool \n",
" 14 source_0726 822558 non-null bool \n",
" 15 source_1206 822558 non-null bool \n",
" 16 combined_id_full_manifest 822558 non-null object\n",
"dtypes: bool(3), int64(2), object(12)\n",
"memory usage: 96.5+ MB\n"
]
}
],
"source": [
"# archive has replaced cargo\n",
"# full manifest or manifest redownload to replace manifest checksums -- they are equal\n",
"links_mismatch = links_manifest_cargo.loc[links_manifest_cargo[\"combined_id_archive\"] != links_manifest_cargo[\"combined_id_full_manifest\"]]\n",
"links_mismatch.info(show_counts = True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There are 42 more mismatched entries. Only 13 additional unique images (MD5s)."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"md5_archive 624574\n",
"combined_id_full_manifest 712540\n",
"combined_id_archive 703446\n",
"dtype: int64"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"links_mismatch[[\"md5_archive\", \"combined_id_full_manifest\", \"combined_id_archive\"]].nunique()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"# This is archive manifest mismatch\n",
"links_mismatch.to_csv(\"../data/links_archive_manifest_IDmismatch.csv\", index = False)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"catalog = pd.read_csv(TOL_FILEPATH + \"catalog.csv\", low_memory=False)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"# remove train_small and all non-EOL entries\n",
"catalog = catalog.loc[catalog.split != \"train_small\"]\n",
"eol_catalog = catalog.loc[catalog.eol_content_id.notna()]"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"split 2\n",
"treeoflife_id 6250420\n",
"eol_content_id 6250420\n",
"eol_page_id 503589\n",
"dtype: int64"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"eol_catalog[list(eol_catalog.columns)[:4]].nunique()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"eol_cols = [col for col in list(eol_catalog.columns) if \"bioscan\" not in col and \"inat\" not in col]"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 6250420 entries, 956715 to 11000930\n",
"Data columns (total 12 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 split 6250420 non-null object \n",
" 1 treeoflife_id 6250420 non-null object \n",
" 2 eol_content_id 6250420 non-null float64\n",
" 3 eol_page_id 6250420 non-null float64\n",
" 4 kingdom 5989611 non-null object \n",
" 5 phylum 5991207 non-null object \n",
" 6 class 5971438 non-null object \n",
" 7 order 5965299 non-null object \n",
" 8 family 5948728 non-null object \n",
" 9 genus 5940313 non-null object \n",
" 10 species 5951613 non-null object \n",
" 11 common 6250420 non-null object \n",
"dtypes: float64(2), object(10)\n",
"memory usage: 619.9+ MB\n"
]
}
],
"source": [
"eol_catalog = eol_catalog[eol_cols]\n",
"eol_catalog.info(show_counts=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Must recast IDs as `int64`"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 6250420 entries, 956715 to 11000930\n",
"Data columns (total 4 columns):\n",
" # Column Dtype \n",
"--- ------ ----- \n",
" 0 split object\n",
" 1 treeoflife_id object\n",
" 2 eol_content_id int64 \n",
" 3 eol_page_id int64 \n",
"dtypes: int64(2), object(2)\n",
"memory usage: 238.4+ MB\n"
]
}
],
"source": [
"eol_catalog = eol_catalog.astype({\"eol_content_id\": \"int64\", \"eol_page_id\": \"int64\"})\n",
"eol_catalog[eol_cols[:4]].info()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"lines_to_next_cell": 2
},
"outputs": [],
"source": [
"# make combined ID for catalog and add suffix to eol content and page IDs\n",
"eol_catalog['combined_id_catalog'] = eol_catalog['eol_content_id'].astype(str) + '_' + eol_catalog['eol_page_id'].astype(str)\n",
"eol_catalog.rename(columns={'eol_content_id': 'eol_content_id_catalog', 'eol_page_id': 'eol_page_id_catalog'}, inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"6219674"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"matched_catalog_ids = list(links_inner.combined_id_catalog.unique())\n",
"len(matched_catalog_ids)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here we go, we got an additional 630 matched IDs!"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['29538374_65414274',\n",
" '27793900_888015',\n",
" '29121641_5618956',\n",
" '27596176_607817',\n",
" '20300703_267922']"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"matched_catalog_ids[:5]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We still have about 30K unmatched (as shown below, it's down to 30,746 from 31,376), let's find those in the catalog and then we'll try to merge with our mismatched cargo & manifest."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5842839 28875844_579175\n",
"7715090 21712402_702458\n",
"10112940 27938371_3091824\n",
"8606944 27597441_49820955\n",
"1247592 14852900_2896866\n",
"Name: combined_id_catalog, dtype: object"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"eol_catalog['combined_id_catalog'].sample(5)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 30746 entries, 956874 to 10996978\n",
"Data columns (total 13 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 split 30746 non-null object\n",
" 1 treeoflife_id 30746 non-null object\n",
" 2 eol_content_id_catalog 30746 non-null int64 \n",
" 3 eol_page_id_catalog 30746 non-null int64 \n",
" 4 kingdom 30573 non-null object\n",
" 5 phylum 30578 non-null object\n",
" 6 class 30153 non-null object\n",
" 7 order 30528 non-null object\n",
" 8 family 30294 non-null object\n",
" 9 genus 30192 non-null object\n",
" 10 species 29399 non-null object\n",
" 11 common 30746 non-null object\n",
" 12 combined_id_catalog 30746 non-null object\n",
"dtypes: int64(2), object(11)\n",
"memory usage: 3.3+ MB\n"
]
}
],
"source": [
"mismatched_catalog = eol_catalog.loc[~eol_catalog[\"combined_id_catalog\"].isin(matched_catalog_ids)]\n",
"mismatched_catalog.info(show_counts = True)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"split 2\n",
"treeoflife_id 30746\n",
"eol_content_id_catalog 30746\n",
"eol_page_id_catalog 7042\n",
"kingdom 7\n",
"phylum 33\n",
"class 87\n",
"order 355\n",
"family 1165\n",
"genus 3503\n",
"species 5174\n",
"common 6884\n",
"combined_id_catalog 30746\n",
"dtype: int64"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mismatched_catalog.nunique()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Seems one class got resolved (equals more orders and down)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Merge with Mismatched CargoArchive-Manifest\n",
"\n",
"let's merge with `links_mismatch` to see if the mismatched archive and manifest combined IDs can be linked up."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 0 entries\n",
"Data columns (total 30 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 split 0 non-null object\n",
" 1 treeoflife_id 0 non-null object\n",
" 2 eol_content_id_catalog 0 non-null int64 \n",
" 3 eol_page_id_catalog 0 non-null int64 \n",
" 4 kingdom 0 non-null object\n",
" 5 phylum 0 non-null object\n",
" 6 class 0 non-null object\n",
" 7 order 0 non-null object\n",
" 8 family 0 non-null object\n",
" 9 genus 0 non-null object\n",
" 10 species 0 non-null object\n",
" 11 common 0 non-null object\n",
" 12 combined_id_catalog 0 non-null object\n",
" 13 filename_archive 0 non-null object\n",
" 14 md5_archive 0 non-null object\n",
" 15 combined_id_archive 0 non-null object\n",
" 16 filename_manifest 0 non-null object\n",
" 17 md5_combined_manifest 0 non-null object\n",
" 18 combined_id_manifest_redownload 0 non-null object\n",
" 19 eol_content_id 0 non-null int64 \n",
" 20 eol_page_id 0 non-null int64 \n",
" 21 medium_source_url 0 non-null object\n",
" 22 eol_full_size_copy_url 0 non-null object\n",
" 23 license_name 0 non-null object\n",
" 24 copyright_owner 0 non-null object\n",
" 25 expected_image_filename 0 non-null object\n",
" 26 source_0706 0 non-null bool \n",
" 27 source_0726 0 non-null bool \n",
" 28 source_1206 0 non-null bool \n",
" 29 combined_id_full_manifest 0 non-null object\n",
"dtypes: bool(3), int64(4), object(23)\n",
"memory usage: 132.0+ bytes\n"
]
}
],
"source": [
"# replace manifest checksums with full manifest as above\n",
"links_catalog_mismatch = pd.merge(mismatched_catalog,\n",
" links_mismatch,\n",
" left_on = \"combined_id_catalog\",\n",
" right_on = \"combined_id_full_manifest\",\n",
" how = \"inner\")\n",
"links_catalog_mismatch.info(show_counts = True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now there's no gain from the mismatch file, but that was only 29 images, so we've captured them from the archive (plus more!)."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"2003559 15270321_240065\n",
"8751466 29485627_17806\n",
"4818957 27965287_35726\n",
"8697796 9483753_328724\n",
"1049389 9446784_5019858\n",
"8364678 9467133_2925218\n",
"5119903 28880812_10305215\n",
"Name: combined_id_catalog, dtype: object"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mismatched_catalog.combined_id_catalog.sample(7)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These pages are reasonably full too: [5660435](https://eol.org/pages/5660435)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Final Catalog\n",
"\n",
"Our final EOL catalog is thus going to be the `treeoflife_id`s in `links_inner`.\n",
"\n",
"Finall question is just how does this look for our `train_small`?"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 593764 entries, 0 to 918500\n",
"Data columns (total 12 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 split 593764 non-null object \n",
" 1 treeoflife_id 593764 non-null object \n",
" 2 eol_content_id 593764 non-null float64\n",
" 3 eol_page_id 593764 non-null float64\n",
" 4 kingdom 569128 non-null object \n",
" 5 phylum 569285 non-null object \n",
" 6 class 567356 non-null object \n",
" 7 order 566839 non-null object \n",
" 8 family 565269 non-null object \n",
" 9 genus 564605 non-null object \n",
" 10 species 565399 non-null object \n",
" 11 common 593764 non-null object \n",
"dtypes: float64(2), object(10)\n",
"memory usage: 58.9+ MB\n"
]
}
],
"source": [
"cat_2 = pd.read_csv(TOL_FILEPATH + \"catalog.csv\", low_memory=False)\n",
"\n",
"# reduce to just train_small and all non-EOL entries\n",
"cat_2 = cat_2.loc[cat_2.split == \"train_small\"]\n",
"eol_cat_2 = cat_2.loc[cat_2.eol_content_id.notna()]\n",
"\n",
"eol_cat_2 = eol_cat_2[eol_cols]\n",
"eol_cat_2.info(show_counts=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So `train_small` has 593,764 images from EOL. \n",
"\n",
"Let's recast IDs as ints to match up with `links_inner` and check we have info for all of them."
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 593764 entries, 0 to 918500\n",
"Data columns (total 4 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 split 593764 non-null object\n",
" 1 treeoflife_id 593764 non-null object\n",
" 2 eol_content_id 593764 non-null int64 \n",
" 3 eol_page_id 593764 non-null int64 \n",
"dtypes: int64(2), object(2)\n",
"memory usage: 22.7+ MB\n"
]
}
],
"source": [
"eol_cat_2 = eol_cat_2.astype({\"eol_content_id\": \"int64\", \"eol_page_id\": \"int64\"})\n",
"eol_cat_2[eol_cols[:4]].info()"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [],
"source": [
"# make combined ID for catalog and add suffix to eol content and page IDs\n",
"eol_cat_2['combined_id_catalog'] = eol_cat_2['eol_content_id'].astype(str) + '_' + eol_cat_2['eol_page_id'].astype(str)\n",
"eol_cat_2.rename(columns={'eol_content_id': 'eol_content_id_catalog', 'eol_page_id': 'eol_page_id_catalog'}, inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 612614 entries, 0 to 612613\n",
"Data columns (total 25 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 split 612614 non-null object\n",
" 1 treeoflife_id 612614 non-null object\n",
" 2 eol_content_id_catalog 612614 non-null int64 \n",
" 3 eol_page_id_catalog 612614 non-null int64 \n",
" 4 kingdom 584979 non-null object\n",
" 5 phylum 585140 non-null object\n",
" 6 class 583235 non-null object\n",
" 7 order 582668 non-null object\n",
" 8 family 581082 non-null object\n",
" 9 genus 580464 non-null object\n",
" 10 species 579943 non-null object\n",
" 11 common 612614 non-null object\n",
" 12 combined_id_catalog_x 612614 non-null object\n",
" 13 combined_id_catalog_y 612614 non-null object\n",
" 14 filename_manifest 612614 non-null object\n",
" 15 combined_id_manifest_redownload 612614 non-null object\n",
" 16 medium_source_url 612614 non-null object\n",
" 17 eol_full_size_copy_url 612614 non-null object\n",
" 18 license_name 612614 non-null object\n",
" 19 copyright_owner 554029 non-null object\n",
" 20 expected_image_filename 612614 non-null object\n",
" 21 source_0706 612614 non-null bool \n",
" 22 source_0726 612614 non-null bool \n",
" 23 source_1206 612614 non-null bool \n",
" 24 combined_id_full_manifest 612614 non-null object\n",
"dtypes: bool(3), int64(2), object(20)\n",
"memory usage: 104.6+ MB\n"
]
}
],
"source": [
"eol_ts_links = pd.merge(eol_cat_2,\n",
" links_inner[list(links_inner.columns)[18:]],\n",
" left_on = \"combined_id_catalog\",\n",
" right_on = \"combined_id_full_manifest\",\n",
" how = \"inner\")\n",
"eol_ts_links.info(show_counts = True)"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"590730"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"eol_ts_links.treeoflife_id.nunique()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So we are missing the metadata for 3,734 of these images."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Check on Rare Species Catalog"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 12000 entries, 0 to 11999\n",
"Data columns (total 11 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 rarespecies_id 12000 non-null object\n",
" 1 eol_content_id 12000 non-null int64 \n",
" 2 eol_page_id 12000 non-null int64 \n",
" 3 kingdom 12000 non-null object\n",
" 4 phylum 12000 non-null object\n",
" 5 class 12000 non-null object\n",
" 6 order 12000 non-null object\n",
" 7 family 12000 non-null object\n",
" 8 genus 12000 non-null object\n",
" 9 species 12000 non-null object\n",
" 10 sciName 12000 non-null object\n",
"dtypes: int64(2), object(9)\n",
"memory usage: 1.0+ MB\n"
]
}
],
"source": [
"rs_catalog = pd.read_csv(\"../../rare_species/data/rarespecies-catalog.csv\",\n",
" low_memory=False,\n",
" dtype = {\"eol_content_id\": \"int64\", \"eol_page_id\": \"int64\"})\n",
"rs_catalog.info(show_counts = True)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"rs_catalog[\"combined_id_rs\"] = rs_catalog[\"eol_content_id\"].astype(str) + \"_\" + rs_catalog[\"eol_page_id\"].astype(str)\n",
"rs_catalog.rename(columns={'eol_content_id': 'eol_content_id_rs', 'eol_page_id': 'eol_page_id_rs'}, inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 12552 entries, 0 to 12551\n",
"Data columns (total 29 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 rarespecies_id 12552 non-null object\n",
" 1 eol_content_id_rs 12552 non-null int64 \n",
" 2 eol_page_id_rs 12552 non-null int64 \n",
" 3 kingdom 12552 non-null object\n",
" 4 phylum 12552 non-null object\n",
" 5 class 12552 non-null object\n",
" 6 order 12552 non-null object\n",
" 7 family 12552 non-null object\n",
" 8 genus 12552 non-null object\n",
" 9 species 12552 non-null object\n",
" 10 sciName 12552 non-null object\n",
" 11 combined_id_rs 12552 non-null object\n",
" 12 filename_archive 12552 non-null object\n",
" 13 md5_archive 12552 non-null object\n",
" 14 combined_id_archive 12552 non-null object\n",
" 15 filename_manifest 12552 non-null object\n",
" 16 md5_combined_manifest 12552 non-null object\n",
" 17 combined_id_manifest_redownload 12552 non-null object\n",
" 18 eol_content_id 12552 non-null int64 \n",
" 19 eol_page_id 12552 non-null int64 \n",
" 20 medium_source_url 12552 non-null object\n",
" 21 eol_full_size_copy_url 12552 non-null object\n",
" 22 license_name 12552 non-null object\n",
" 23 copyright_owner 11171 non-null object\n",
" 24 expected_image_filename 12552 non-null object\n",
" 25 source_0706 12552 non-null bool \n",
" 26 source_0726 12552 non-null bool \n",
" 27 source_1206 12552 non-null bool \n",
" 28 combined_id_full_manifest 12552 non-null object\n",
"dtypes: bool(3), int64(4), object(22)\n",
"memory usage: 2.5+ MB\n"
]
}
],
"source": [
"rs_links = pd.merge(rs_catalog,\n",
" links_manifest_cargo,\n",
" left_on = \"combined_id_rs\",\n",
" right_on = \"combined_id_archive\", # looking at archive\n",
" how = \"inner\")\n",
"rs_links.info(show_counts = True)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"rarespecies_id 11826\n",
"eol_content_id_rs 11826\n",
"eol_page_id_rs 400\n",
"kingdom 1\n",
"phylum 5\n",
"class 15\n",
"order 85\n",
"family 202\n",
"genus 316\n",
"species 385\n",
"sciName 400\n",
"combined_id_rs 11826\n",
"filename_archive 11826\n",
"md5_archive 11663\n",
"combined_id_archive 11826\n",
"filename_manifest 12221\n",
"md5_combined_manifest 11663\n",
"combined_id_manifest_redownload 12221\n",
"eol_content_id 12221\n",
"eol_page_id 447\n",
"medium_source_url 12056\n",
"eol_full_size_copy_url 12119\n",
"license_name 15\n",
"copyright_owner 3724\n",
"expected_image_filename 12221\n",
"source_0706 2\n",
"source_0726 2\n",
"source_1206 2\n",
"combined_id_full_manifest 12221\n",
"dtype: int64"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rs_links.nunique()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's check the mismatched cargo/manifest entries for those last 174..."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"11826"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"matched_rs_ids = list(rs_links.combined_id_rs.unique())\n",
"len(matched_rs_ids)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['22519448_914532',\n",
" '28677580_1057176',\n",
" '20714475_47047909',\n",
" '29975068_45509269']"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"matched_rs_ids[:4]"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1473 29538601_46580048\n",
"11127 29447084_1019571\n",
"6578 20398296_328017\n",
"11583 29772112_1049135\n",
"Name: combined_id_rs, dtype: object"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rs_catalog[\"combined_id_rs\"].sample(4)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 174 entries, 163 to 11990\n",
"Data columns (total 12 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 rarespecies_id 174 non-null object\n",
" 1 eol_content_id_rs 174 non-null int64 \n",
" 2 eol_page_id_rs 174 non-null int64 \n",
" 3 kingdom 174 non-null object\n",
" 4 phylum 174 non-null object\n",
" 5 class 174 non-null object\n",
" 6 order 174 non-null object\n",
" 7 family 174 non-null object\n",
" 8 genus 174 non-null object\n",
" 9 species 174 non-null object\n",
" 10 sciName 174 non-null object\n",
" 11 combined_id_rs 174 non-null object\n",
"dtypes: int64(2), object(10)\n",
"memory usage: 17.7+ KB\n"
]
}
],
"source": [
"mismatched_rs = rs_catalog.loc[~rs_catalog[\"combined_id_rs\"].isin(matched_rs_ids)]\n",
"mismatched_rs.info(show_counts = True)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 0 entries\n",
"Data columns (total 29 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 rarespecies_id 0 non-null object\n",
" 1 eol_content_id_rs 0 non-null int64 \n",
" 2 eol_page_id_rs 0 non-null int64 \n",
" 3 kingdom 0 non-null object\n",
" 4 phylum 0 non-null object\n",
" 5 class 0 non-null object\n",
" 6 order 0 non-null object\n",
" 7 family 0 non-null object\n",
" 8 genus 0 non-null object\n",
" 9 species 0 non-null object\n",
" 10 sciName 0 non-null object\n",
" 11 combined_id_rs 0 non-null object\n",
" 12 filename_archive 0 non-null object\n",
" 13 md5_archive 0 non-null object\n",
" 14 combined_id_archive 0 non-null object\n",
" 15 filename_manifest 0 non-null object\n",
" 16 md5_combined_manifest 0 non-null object\n",
" 17 combined_id_manifest_redownload 0 non-null object\n",
" 18 eol_content_id 0 non-null int64 \n",
" 19 eol_page_id 0 non-null int64 \n",
" 20 medium_source_url 0 non-null object\n",
" 21 eol_full_size_copy_url 0 non-null object\n",
" 22 license_name 0 non-null object\n",
" 23 copyright_owner 0 non-null object\n",
" 24 expected_image_filename 0 non-null object\n",
" 25 source_0706 0 non-null bool \n",
" 26 source_0726 0 non-null bool \n",
" 27 source_1206 0 non-null bool \n",
" 28 combined_id_full_manifest 0 non-null object\n",
"dtypes: bool(3), int64(4), object(22)\n",
"memory usage: 132.0+ bytes\n"
]
}
],
"source": [
"links_rs_mismatch = pd.merge(mismatched_rs,\n",
" links_mismatch,\n",
" left_on = \"combined_id_rs\",\n",
" right_on = \"combined_id_full_manifest\",\n",
" how = \"inner\")\n",
"links_rs_mismatch.info(show_counts = True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"jupytext": {
"formats": "ipynb,py:percent"
},
"kernelspec": {
"display_name": "tol",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
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