diff --git "a/notebooks/BioCLIP_data_viz.ipynb" "b/notebooks/BioCLIP_data_viz.ipynb" new file mode 100644--- /dev/null +++ "b/notebooks/BioCLIP_data_viz.ipynb" @@ -0,0 +1,3250 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import seaborn as sns\n", + "import plotly.express as px\n", + "\n", + "sns.set_style(\"whitegrid\")\n", + "sns.set(rc = {'figure.figsize': (10,10)})" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_222484/3694103411.py:1: DtypeWarning: Columns (4,5,6) have mixed types. Specify dtype option on import or set low_memory=False.\n", + " df = pd.read_csv(\"../data/v1-dev-names.csv\")\n" + ] + } + ], + "source": [ + "df = pd.read_csv(\"../data/v1-dev-names.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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treeoflife_ideol_content_ideol_page_idbioscan_partbioscan_filenameinat21_filenameinat21_cls_nameinat21_cls_numkingdomphylumclassorderfamilygenusspeciescommon
00824741f-cc1c-4881-b292-15fd3f7964cd29538374.065414274.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNManfredaNaNtuberose
15ca08f6b-9396-4cb9-9283-8dee158aac1827793900.0888015.0NaNNaNNaNNaNNaNMetazoaArthropodaPancrustaceaLepidopteraOenosandridaeDiscophlebialipaugesDiscophlebia lipauges
2f8c0f271-d8e5-4299-92d3-920508f74bf029121641.05618956.0NaNNaNNaNNaNNaNArchaeplastidaTracheophytaNaNSapindalesRutaceaeMelicopedenhamiiMelicope denhamii
31f53e9d1-527f-42fd-b813-9f62fa2c237227596176.0607817.0NaNNaNNaNNaNNaNMetazoaArthropodaPancrustaceaTrichopteraLimnephilidaeLimnephiluslithusLimnephilus lithus
4a05bc2a8-5453-4683-903e-ed44f0fe724520300703.0267922.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNAnatolian Black-eyed Blue
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" + ], + "text/plain": [ + " treeoflife_id eol_content_id eol_page_id \\\n", + "0 0824741f-cc1c-4881-b292-15fd3f7964cd 29538374.0 65414274.0 \n", + "1 5ca08f6b-9396-4cb9-9283-8dee158aac18 27793900.0 888015.0 \n", + "2 f8c0f271-d8e5-4299-92d3-920508f74bf0 29121641.0 5618956.0 \n", + "3 1f53e9d1-527f-42fd-b813-9f62fa2c2372 27596176.0 607817.0 \n", + "4 a05bc2a8-5453-4683-903e-ed44f0fe7245 20300703.0 267922.0 \n", + "\n", + " bioscan_part bioscan_filename inat21_filename inat21_cls_name \\\n", + "0 NaN NaN NaN NaN \n", + "1 NaN NaN NaN NaN \n", + "2 NaN NaN NaN NaN \n", + "3 NaN NaN NaN NaN \n", + "4 NaN NaN NaN NaN \n", + "\n", + " inat21_cls_num kingdom phylum class order \\\n", + "0 NaN NaN NaN NaN NaN \n", + "1 NaN Metazoa Arthropoda Pancrustacea Lepidoptera \n", + "2 NaN Archaeplastida Tracheophyta NaN Sapindales \n", + "3 NaN Metazoa Arthropoda Pancrustacea Trichoptera \n", + "4 NaN NaN NaN NaN NaN \n", + "\n", + " family genus species common \n", + "0 NaN Manfreda NaN tuberose \n", + "1 Oenosandridae Discophlebia lipauges Discophlebia lipauges \n", + "2 Rutaceae Melicope denhamii Melicope denhamii \n", + "3 Limnephilidae Limnephilus lithus Limnephilus lithus \n", + "4 NaN NaN NaN Anatolian Black-eyed Blue " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 10436521 entries, 0 to 10436520\n", + "Data columns (total 16 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 treeoflife_id 10436521 non-null object \n", + " 1 eol_content_id 6621365 non-null float64\n", + " 2 eol_page_id 6621365 non-null float64\n", + " 3 bioscan_part 1128313 non-null float64\n", + " 4 bioscan_filename 1128313 non-null object \n", + " 5 inat21_filename 2686843 non-null object \n", + " 6 inat21_cls_name 2686843 non-null object \n", + " 7 inat21_cls_num 2686843 non-null float64\n", + " 8 kingdom 7734559 non-null object \n", + " 9 phylum 7732689 non-null object \n", + " 10 class 6657484 non-null object \n", + " 11 order 7690349 non-null object \n", + " 12 family 7706759 non-null object \n", + " 13 genus 8060829 non-null object \n", + " 14 species 7179863 non-null object \n", + " 15 common 10436521 non-null object \n", + "dtypes: float64(4), object(12)\n", + "memory usage: 1.2+ GB\n" + ] + } + ], + "source": [ + "df.info(show_counts = True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Do we truly have common name labeled for all images?\n", + "\n", + "Sometimes it is the scientific name." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "treeoflife_id 10436521\n", + "eol_content_id 6621365\n", + "eol_page_id 570515\n", + "bioscan_part 113\n", + "bioscan_filename 1128313\n", + "inat21_filename 2686843\n", + "inat21_cls_name 10000\n", + "inat21_cls_num 10000\n", + "kingdom 5\n", + "phylum 49\n", + "class 136\n", + "order 766\n", + "family 5665\n", + "genus 89914\n", + "species 189846\n", + "common 527316\n", + "dtype: int64" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.nunique()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['kingdom', 'phylum', 'class', 'order', 'family', 'genus', 'species']" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "taxa = list(df.columns[8:15])\n", + "taxa" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Check the number of images with all 7 taxonomic labels." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Index: 6657484 entries, 1 to 10436518\n", + "Data columns (total 7 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 kingdom 6657484 non-null object\n", + " 1 phylum 6657484 non-null object\n", + " 2 class 6657484 non-null object\n", + " 3 order 6615972 non-null object\n", + " 4 family 6630424 non-null object\n", + " 5 genus 5691848 non-null object\n", + " 6 species 5267629 non-null object\n", + "dtypes: object(7)\n", + "memory usage: 406.3+ MB\n" + ] + } + ], + "source": [ + "# Class has least non-null entries, so we'll start by filtering it out\n", + "df_all_taxa = df.loc[df['class'].notna()]\n", + "df_all_taxa[taxa].info(show_counts = True)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Index: 5267629 entries, 1 to 10436518\n", + "Data columns (total 7 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 kingdom 5267629 non-null object\n", + " 1 phylum 5267629 non-null object\n", + " 2 class 5267629 non-null object\n", + " 3 order 5233623 non-null object\n", + " 4 family 5261785 non-null object\n", + " 5 genus 5267456 non-null object\n", + " 6 species 5267629 non-null object\n", + "dtypes: object(7)\n", + "memory usage: 321.5+ MB\n" + ] + } + ], + "source": [ + "# Now species has least non-null values\n", + "df_all_taxa = df_all_taxa.loc[df_all_taxa['species'].notna()]\n", + "df_all_taxa[taxa].info(show_counts = True)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Index: 5233623 entries, 1 to 10436518\n", + "Data columns (total 7 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 kingdom 5233623 non-null object\n", + " 1 phylum 5233623 non-null object\n", + " 2 class 5233623 non-null object\n", + " 3 order 5233623 non-null object\n", + " 4 family 5228644 non-null object\n", + " 5 genus 5233450 non-null object\n", + " 6 species 5233623 non-null object\n", + "dtypes: object(7)\n", + "memory usage: 319.4+ MB\n" + ] + } + ], + "source": [ + "# Now order has least non-null values \n", + "df_all_taxa = df_all_taxa.loc[df_all_taxa['order'].notna()]\n", + "df_all_taxa[taxa].info(show_counts = True)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Index: 5228644 entries, 1 to 10436518\n", + "Data columns (total 7 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 kingdom 5228644 non-null object\n", + " 1 phylum 5228644 non-null object\n", + " 2 class 5228644 non-null object\n", + " 3 order 5228644 non-null object\n", + " 4 family 5228644 non-null object\n", + " 5 genus 5228471 non-null object\n", + " 6 species 5228644 non-null object\n", + "dtypes: object(7)\n", + "memory usage: 319.1+ MB\n" + ] + } + ], + "source": [ + "# Now family has least non-null values\n", + "df_all_taxa = df_all_taxa.loc[df_all_taxa['family'].notna()]\n", + "df_all_taxa[taxa].info(show_counts = True)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Index: 5228471 entries, 1 to 10436518\n", + "Data columns (total 7 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 kingdom 5228471 non-null object\n", + " 1 phylum 5228471 non-null object\n", + " 2 class 5228471 non-null object\n", + " 3 order 5228471 non-null object\n", + " 4 family 5228471 non-null object\n", + " 5 genus 5228471 non-null object\n", + " 6 species 5228471 non-null object\n", + "dtypes: object(7)\n", + "memory usage: 319.1+ MB\n" + ] + } + ], + "source": [ + "# Finally, genus is the only one with null values\n", + "df_all_taxa = df_all_taxa.loc[df_all_taxa['genus'].notna()]\n", + "df_all_taxa[taxa].info(show_counts = True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We have 5,228,471 images with full taxonomic labels." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Distributions\n", + "\n", + "Work through larger number of unique taxa here, on server. Also, make `df_taxa` with just taxa columns so it's smaller to process faster.\n", + "\n", + "All in format `num_lowerTaxon_higherTaxon`." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "df_taxa = df[taxa]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Species per higher order taxa will take longest." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's start with the taxa that have more unique values under kingdom to see where the server's at on speed too." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "num_families_kingdom = {}\n", + "num_genera_kingdom = {}\n", + "num_species_kingdom = {}\n", + "for kingdom in df_taxa.kingdom.unique():\n", + " temp = df_taxa.loc[df_taxa.kingdom == kingdom]\n", + " num_families_kingdom[kingdom] = temp.family.nunique()\n", + " num_genera_kingdom[kingdom] = temp['genus'].nunique()\n", + " num_species_kingdom[kingdom] = temp['species'].nunique()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{nan: 0,\n", + " 'Metazoa': 4272,\n", + " 'Archaeplastida': 719,\n", + " 'Fungi': 468,\n", + " 'Animalia': 1077,\n", + " 'Plantae': 286}" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "num_families_kingdom" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Seems reasonable, let's get the larger of the higher class ones going, so check genus and species counts within families." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "num_genera_family = {}\n", + "num_species_family = {}\n", + "for family in df_taxa.family.unique():\n", + " temp = df_taxa.loc[df_taxa.family == family]\n", + " num_genera_family[family] = temp['genus'].nunique()\n", + " num_species_family[family] = temp['species'].nunique()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Get counts for everything below order." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "num_families_order = {}\n", + "num_genera_order = {}\n", + "num_species_order = {}\n", + "for order in df_taxa.order.unique():\n", + " temp = df_taxa.loc[df_taxa.order == order]\n", + " num_families_order[order] = temp['family'].nunique()\n", + " num_genera_order[order] = temp['genus'].nunique()\n", + " num_species_order[order] = temp['species'].nunique()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{nan: 0,\n", + " 'Lepidoptera': 128,\n", + " 'Sapindales': 9,\n", + " 'Trichoptera': 38,\n", + " 'Hemiptera': 135,\n", + " 'Coleoptera': 150,\n", + " 'Squamata': 54,\n", + " 'Tetraodontiformes': 10,\n", + " 'Mantodea': 31,\n", + " 'Heterobranchia': 43,\n", + " 'Lamiales': 24,\n", + " 'Fabales': 4,\n", + " 'Asterales': 10,\n", + " 'Carangiformes': 5,\n", + " 'Piperales': 3,\n", + " 'Caryophyllales': 39,\n", + " 'Boletales': 18,\n", + " 'Characiformes': 23,\n", + " 'Poales': 14,\n", + " 'Arecales': 2,\n", + " 'Malpighiales': 32,\n", + " 'Anura': 61,\n", + " 'Agaricales': 33,\n", + " 'Magnoliales': 5,\n", + " 'Hymenoptera': 101,\n", + " 'Littorinimorpha': 64,\n", + " 'Sessilia': 11,\n", + " 'Labriformes': 1,\n", + " 'Ricinulei': 1,\n", + " 'Helotiales': 18,\n", + " 'Asparagales': 13,\n", + " 'Proteales': 4,\n", + " 'Araneae': 111,\n", + " 'Polypodiales': 25,\n", + " 'Saurischia': 265,\n", + " 'Ulotrichales': 1,\n", + " 'Solanales': 5,\n", + " 'Diptera': 141,\n", + " 'Caudata': 9,\n", + " 'Saxifragales': 14,\n", + " 'Therapsida': 178,\n", + " 'Polyporales': 13,\n", + " 'Myrtales': 7,\n", + " 'Rosales': 8,\n", + " 'Decapoda': 78,\n", + " 'Phasmida': 13,\n", + " 'Imparidentia': 17,\n", + " 'Gobiiformes': 9,\n", + " 'Neogastropoda': 46,\n", + " 'Brassicales': 17,\n", + " 'Rhabdocoela': 32,\n", + " 'Cypriniformes': 275,\n", + " 'Orectolobiformes': 7,\n", + " 'Spariformes': 3,\n", + " 'Gentianales': 5,\n", + " 'Alismatales': 13,\n", + " 'Malvales': 11,\n", + " 'Pinales': 8,\n", + " 'Bryales': 13,\n", + " 'Nudipleura': 8,\n", + " 'Clupeiformes': 5,\n", + " 'Ericales': 21,\n", + " 'Chitonida': 12,\n", + " 'Apiales': 7,\n", + " 'Sebacinales': 1,\n", + " 'Lecanorales': 16,\n", + " 'Pertusariales': 4,\n", + " 'Commelinales': 5,\n", + " 'Orthoptera': 36,\n", + " 'Fagales': 7,\n", + " 'Dipsacales': 3,\n", + " 'Comatulida': 21,\n", + " 'Liliales': 11,\n", + " 'Monostilifera': 10,\n", + " 'Perciformes': 88,\n", + " 'Erysiphales': 1,\n", + " 'Ephippiformes': 2,\n", + " 'Carybdeida': 5,\n", + " 'Eurotiales': 3,\n", + " 'Odonata': 37,\n", + " 'Teloschistales': 3,\n", + " 'Russulales': 11,\n", + " 'Heteroscleromorpha': 17,\n", + " 'Polyzoniida': 3,\n", + " 'Stolidobranchia': 3,\n", + " 'Geraniales': 2,\n", + " 'Cyprinodontiformes': 10,\n", + " 'Chromadorea': 12,\n", + " 'Lophiiformes': 15,\n", + " 'Aquifoliales': 5,\n", + " 'Valvatacea': 3,\n", + " 'Gloeophyllales': 1,\n", + " 'Pezizales': 14,\n", + " 'Rhodymeniales': 6,\n", + " 'Neuroptera': 14,\n", + " 'Pteriomorphia': 12,\n", + " 'Trochida': 13,\n", + " 'Lutjanidae': 21,\n", + " 'Ranunculales': 7,\n", + " 'Salmoniformes': 1,\n", + " 'Megaloptera': 2,\n", + " 'Desmidiales': 4,\n", + " 'Octocorallia': 6,\n", + " 'Aulopiformes': 19,\n", + " 'Semaeostomeae': 5,\n", + " 'Ophiurida': 3,\n", + " 'Ixodida': 2,\n", + " 'Carcharhiniformes': 8,\n", + " 'Blattodea': 16,\n", + " 'Pandanales': 5,\n", + " 'Xylariales': 16,\n", + " 'Synallactida': 3,\n", + " 'Opiliones': 52,\n", + " 'Blenniiformes': 6,\n", + " 'Corticiales': 1,\n", + " 'Forcipulatacea': 2,\n", + " 'Kurtiformes': 2,\n", + " 'Syngnathiformes': 10,\n", + " 'Ephemeroptera': 25,\n", + " 'Bdelloidea': 4,\n", + " 'Orthotrichales': 2,\n", + " 'Hydroidolina': 9,\n", + " 'Santalales': 8,\n", + " 'Boraginales': 1,\n", + " 'Lycopodiales': 1,\n", + " 'Scleractinia': 26,\n", + " 'Siluriformes': 36,\n", + " 'Lepisosteiformes': 1,\n", + " 'Atheriniformes': 38,\n", + " 'Scombriformes': 16,\n", + " 'Gomphales': 3,\n", + " 'Testudines': 12,\n", + " 'Acanthuriformes': 3,\n", + " 'Carinacea': 4,\n", + " 'Gobiesociformes': 1,\n", + " 'Zingiberales': 8,\n", + " 'Pleuronectiformes': 13,\n", + " 'Microbotryales': 1,\n", + " 'Dermaptera': 8,\n", + " 'Capnodiales': 6,\n", + " 'Trentepohliales': 1,\n", + " 'Dicranales': 8,\n", + " 'Ulvales': 3,\n", + " 'Cycloneritida': 6,\n", + " 'Dilleniales': 1,\n", + " 'Hymenophyllales': 1,\n", + " 'Zygentoma': 2,\n", + " 'Nymphaeales': 3,\n", + " 'Phlebobranchia': 6,\n", + " 'Anguilliformes': 17,\n", + " 'Entomophaga': 0,\n", + " 'Pucciniales': 14,\n", + " 'Ceramiales': 7,\n", + " 'Isopoda': 49,\n", + " 'Holothuriida': 2,\n", + " 'Lichinales': 3,\n", + " 'Lepadiformes': 4,\n", + " 'Hypnales': 19,\n", + " 'Verongimorpha': 3,\n", + " 'Scorpiones': 15,\n", + " 'Actiniaria': 9,\n", + " 'Cichliformes': 2,\n", + " 'Marchantiidae': 3,\n", + " 'Laurales': 7,\n", + " 'Carditida': 4,\n", + " 'Cantharellales': 7,\n", + " 'Funariales': 6,\n", + " 'Tetraphidales': 2,\n", + " 'Raphidioptera': 2,\n", + " 'Palaeoheterodonta': 3,\n", + " 'Ploima': 20,\n", + " 'Plecoptera': 12,\n", + " 'Amphipoda': 51,\n", + " 'Marattiales': 1,\n", + " 'Cucurbitales': 8,\n", + " 'Haemulidae': 16,\n", + " 'Rhizostomeae': 3,\n", + " 'Embioptera': 8,\n", + " 'Harpacticoida': 32,\n", + " 'Rhynchobdellida': 2,\n", + " 'Chaetodontiformes': 2,\n", + " 'Oxalidales': 7,\n", + " 'Collothecacea': 2,\n", + " 'Salviniales': 2,\n", + " 'Tubeufiales': 1,\n", + " 'Seguenziida': 6,\n", + " 'Psilotales': 1,\n", + " 'Stauromedusae': 4,\n", + " 'Polydesmida': 16,\n", + " 'Halymeniales': 1,\n", + " 'Mecoptera': 7,\n", + " 'Laboulbeniales': 1,\n", + " 'Anabantiformes': 7,\n", + " 'Escalloniales': 1,\n", + " 'Rhizopodaceae': 1,\n", + " 'Hypocreales': 9,\n", + " 'Ophioglossales': 1,\n", + " 'Siphonaptera': 8,\n", + " 'Metzgeriidae': 2,\n", + " 'Beryciformes': 16,\n", + " 'Centrarchiformes': 24,\n", + " 'Selaginellales': 1,\n", + " 'Zygophyllales': 2,\n", + " 'Notostraca': 1,\n", + " 'Acoela': 16,\n", + " 'Squaliformes': 7,\n", + " 'Amphilepidida': 7,\n", + " 'Exobasidiales': 4,\n", + " 'Gigartinales': 26,\n", + " 'Celastrales': 2,\n", + " 'Acipenseriformes': 2,\n", + " 'Dasycladales': 2,\n", + " 'Gymnotiformes': 5,\n", + " 'Rajiformes': 3,\n", + " 'Diaporthales': 7,\n", + " 'Myliobatiformes': 9,\n", + " 'Geastrales': 1,\n", + " 'Phallales': 2,\n", + " 'Psocodea': 42,\n", + " 'Ephedrales': 1,\n", + " 'Gymnophiona': 9,\n", + " 'Spinulosacea': 1,\n", + " 'Jungermanniidae': 1,\n", + " 'Cheilostomatida': 60,\n", + " 'Lepetellida': 9,\n", + " 'Dioscoreales': 3,\n", + " 'Bruniales': 2,\n", + " 'Protobranchia': 5,\n", + " 'Rhytismatales': 4,\n", + " 'Candelariales': 1,\n", + " 'Cornales': 7,\n", + " 'Platydesmida': 1,\n", + " 'Peltigerales': 9,\n", + " 'Squatiniformes': 1,\n", + " 'Hymenochaetales': 4,\n", + " 'Cyatheales': 7,\n", + " 'Dictyoceratida': 4,\n", + " 'Irregularia': 4,\n", + " 'Seligeriaceae': 3,\n", + " 'Phyllodocida': 19,\n", + " 'Lamniformes': 6,\n", + " 'Auriculariales': 2,\n", + " 'Atelostomata': 7,\n", + " 'Calcinea': 1,\n", + " 'Calcaronea': 2,\n", + " 'Glomerellales': 2,\n", + " 'Leucodontaceae': 6,\n", + " 'Platyctenida': 2,\n", + " 'Crocodylia': 2,\n", + " 'Priacanthidae': 4,\n", + " 'Apodida': 3,\n", + " 'Architaenioglossa': 9,\n", + " 'Trombidiformes': 16,\n", + " 'Sordariales': 4,\n", + " 'Zoantharia': 7,\n", + " 'Icacinales': 1,\n", + " 'Cyclopoida': 35,\n", + " 'Gadiformes': 16,\n", + " 'Trachylinae': 3,\n", + " 'Tremellales': 6,\n", + " 'Enoplea': 6,\n", + " 'Cycadales': 2,\n", + " 'Myxiniformes': 1,\n", + " 'Stomatopoda': 3,\n", + " 'Charales': 1,\n", + " 'Furia': 0,\n", + " 'Beloniformes': 5,\n", + " 'Symphypleona': 6,\n", + " 'Uranoscopiformes': 4,\n", + " 'Octopoda': 13,\n", + " 'Amblypygi': 3,\n", + " 'Mycosphaerellaceae': 20,\n", + " 'Verrucariales': 1,\n", + " 'Sphaeropleales': 7,\n", + " 'Cidaroida': 4,\n", + " 'Arthoniales': 4,\n", + " 'Sphagnales': 1,\n", + " 'Entomobryomorpha': 4,\n", + " 'Petrosaviales': 1,\n", + " 'Osmundales': 1,\n", + " 'Thelephorales': 2,\n", + " 'Pleosporales': 24,\n", + " 'Bryopsidales': 6,\n", + " 'Plocamiales': 1,\n", + " 'Synbranchiformes': 4,\n", + " 'Mesostigmata': 6,\n", + " 'Julida': 6,\n", + " 'Chaetophorales': 2,\n", + " 'Pelliidae': 3,\n", + " 'Schizomida': 1,\n", + " 'Umbilicariales': 1,\n", + " 'Petromyzontiformes': 3,\n", + " 'Mycocaliciales': 2,\n", + " 'Dendrochirotida': 6,\n", + " 'Vitales': 1,\n", + " 'Monogenea': 5,\n", + " 'Gracilariales': 1,\n", + " 'Isoetales': 1,\n", + " 'Neolectales': 1,\n", + " 'Polypteriformes': 1,\n", + " 'Mugiliformes': 1,\n", + " 'Taphrinales': 1,\n", + " 'Equisetales': 1,\n", + " 'Patellariales': 1,\n", + " 'Tricladida': 9,\n", + " 'Botryosphaeriales': 3,\n", + " 'Pleurostigmophora': 4,\n", + " 'Ptilidiales': 2,\n", + " 'Austrobaileyales': 3,\n", + " 'Euryalida': 3,\n", + " 'Polycladida': 30,\n", + " 'Brachypoda': 1,\n", + " 'Grimmiales': 2,\n", + " 'Calanoida': 29,\n", + " 'Dolichomicrostomida': 2,\n", + " 'Ophiostomatales': 1,\n", + " 'Dacrymycetales': 1,\n", + " 'Holocentriformes': 1,\n", + " 'Xiphosurida': 1,\n", + " 'Gunnerales': 2,\n", + " 'Amphinomida': 2,\n", + " 'Pottiales': 3,\n", + " 'Phyllachorales': 2,\n", + " 'Gerreidae': 8,\n", + " 'Pantopoda': 10,\n", + " 'Argentiniformes': 4,\n", + " 'Prolecithophora': 5,\n", + " 'Pempheriformes': 16,\n", + " 'Polytrichales': 1,\n", + " 'Geoglossales': 1,\n", + " 'Mysida': 2,\n", + " 'Orbiliales': 1,\n", + " 'Trechisporales': 1,\n", + " 'Compsopogonales': 1,\n", + " 'Flosculariaceae': 5,\n", + " 'Chimaeriformes': 3,\n", + " 'Proseriata': 11,\n", + " 'Bangiophyceae': 3,\n", + " 'Onygenales': 4,\n", + " 'Amiiformes': 1,\n", + " 'Ustilaginales': 5,\n", + " 'Aplousobranchia': 10,\n", + " 'Porellales': 4,\n", + " 'Erythropeltidales': 2,\n", + " 'Hapalidiales': 1,\n", + " 'Tanaidacea': 4,\n", + " 'Salpida': 1,\n", + " 'Cestida': 1,\n", + " 'Climaciaceae': 1,\n", + " 'Alepocephaliformes': 2,\n", + " 'Gelidiales': 3,\n", + " 'Acarosporales': 1,\n", + " 'Hildenbrandiales': 1,\n", + " 'Ginkgoales': 1,\n", + " 'Ophiacanthida': 7,\n", + " 'Crassiclitellata': 10,\n", + " 'Phycomycetaceae': 2,\n", + " 'Ophioscolecida': 1,\n", + " 'Grylloblattodea': 1,\n", + " 'Pristiophoriformes': 1,\n", + " 'Crossosomatales': 4,\n", + " 'Heterodontiformes': 1,\n", + " 'Gigantorhynchida': 1,\n", + " 'Chlorellales': 2,\n", + " 'Baeomycetales': 3,\n", + " 'Phymatocerotales': 1,\n", + " 'Hedwigiaceae': 4,\n", + " 'Buxales': 1,\n", + " 'Trematoda': 9,\n", + " 'Sphaerotheriida': 4,\n", + " 'Ophidiiformes': 13,\n", + " 'Schizaeales': 3,\n", + " 'Antipatharia': 6,\n", + " 'Stomiiformes': 4,\n", + " 'Acroechinoidea': 3,\n", + " 'Molpadida': 3,\n", + " 'Sarcoptiformes': 43,\n", + " 'Gnetales': 1,\n", + " 'Pterobryaceae': 5,\n", + " 'Caproidae': 2,\n", + " 'Lampriformes': 6,\n", + " 'Scalpelliformes': 4,\n", + " 'Notostigmophora': 1,\n", + " 'Corallinales': 1,\n", + " 'Fissidentaceae': 1,\n", + " 'Halocyprida': 3,\n", + " 'Meteoriaceae': 5,\n", + " 'Osmeriformes': 4,\n", + " 'Galaxiiformes': 1,\n", + " 'Lingulata': 2,\n", + " 'Cestoda': 9,\n", + " 'Anostraca': 7,\n", + " 'Gleicheniales': 3,\n", + " 'Diplostraca': 14,\n", + " 'Cladophorales': 5,\n", + " 'Corallimorpharia': 3,\n", + " 'Trochodendrales': 1,\n", + " 'Poduromorpha': 5,\n", + " 'Ctenostomatida': 5,\n", + " 'Lobata': 4,\n", + " 'Acorales': 1,\n", + " 'Chordeumatida': 14,\n", + " 'Syzygites': 0,\n", + " 'Asterinales': 2,\n", + " 'Albuliformes': 1,\n", + " 'Hysteriales': 1,\n", + " 'Lophogastrida': 1,\n", + " 'Arhynchobdellida': 11,\n", + " 'Rhinopristiformes': 5,\n", + " 'Venturiales': 1,\n", + " 'Pleurotomariida': 1,\n", + " 'Torpediniformes': 5,\n", + " 'Amphisphaeriales': 5,\n", + " 'Canellales': 2,\n", + " 'Andreaeales': 1,\n", + " 'Palmariales': 4,\n", + " 'Chlamydomonadales': 8,\n", + " 'Entomophthora': 0,\n", + " 'Cyttariales': 1,\n", + " 'Elopiformes': 2,\n", + " 'Neckeraceae': 7,\n", + " 'Paracryphiales': 1,\n", + " 'Pseudoscorpiones': 14,\n", + " 'Urocystidales': 4,\n", + " 'Nanaloricida': 1,\n", + " 'Spirobolida': 10,\n", + " 'Coronatae': 6,\n", + " 'Myodocopida': 3,\n", + " 'Percopsiformes': 3,\n", + " 'Uropygi': 1,\n", + " 'Solifugae': 9,\n", + " 'Thysanoptera': 5,\n", + " 'Doassansiales': 2,\n", + " 'Garryales': 2,\n", + " 'Blasiidae': 1,\n", + " 'Eunicida': 5,\n", + " 'Hiodontiformes': 1,\n", + " 'Hysterangiales': 5,\n", + " 'Hookeriales': 2,\n", + " 'Beroida': 1,\n", + " 'Lyssacinosida': 3,\n", + " 'Notacanthiformes': 2,\n", + " 'Huerteales': 3,\n", + " 'Chaetosphaeriales': 1,\n", + " 'Cryphaeaceae': 1,\n", + " 'Lepidopleurida': 1,\n", + " 'Microascales': 3,\n", + " 'Fecampiida': 5,\n", + " 'Hyocrinida': 1,\n", + " 'Osteoglossiformes': 5,\n", + " 'Chaetothyriales': 2,\n", + " 'Ostropales': 7,\n", + " 'Helicobasidiales': 1,\n", + " 'Cepolidae': 3,\n", + " 'Entylomatales': 1,\n", + " 'Siphonostomatoida': 14,\n", + " 'Coniochaetales': 1,\n", + " 'Cystofilobasidiales': 1,\n", + " 'Istiophoriformes': 2,\n", + " 'Nautilida': 1,\n", + " 'Kickxellaceae': 3,\n", + " 'Neelipleona': 1,\n", + " 'Batrachoidiformes': 1,\n", + " 'Bonnemaisoniales': 2,\n", + " 'Dendroceratida': 2,\n", + " 'Ceriantharia': 2,\n", + " 'Cyclorhagida': 2,\n", + " 'Esociformes': 2,\n", + " 'Atractiellales': 1,\n", + " 'Myctophiformes': 2,\n", + " 'Pyrenulales': 2,\n", + " 'Atheliales': 1,\n", + " 'Mytilinidiales': 2,\n", + " 'Elasipodida': 4,\n", + " 'Notothyladales': 1,\n", + " 'Polymorphida': 1,\n", + " 'Nemastomatales': 2,\n", + " 'Palmophyllales': 1,\n", + " 'Velatida': 3,\n", + " 'Mucoraceae': 7,\n", + " 'Coronophorales': 3,\n", + " 'Nemaliales': 3,\n", + " 'Spirostreptida': 6,\n", + " 'Euphausiacea': 2,\n", + " 'Phomatospora': 0,\n", + " 'Rhynchonellata': 4,\n", + " 'Zeiformes': 14,\n", + " 'Copelata': 2,\n", + " 'Trachichthyiformes': 5,\n", + " 'Strigulales': 1,\n", + " 'Podocopida': 5,\n", + " 'Boliniales': 1,\n", + " 'Zygnematales': 2,\n", + " 'Archaeognatha': 2,\n", + " 'Saccharomycetales': 5,\n", + " 'Phragmophora': 1,\n", + " 'Ornithischia': 9,\n", + " 'Tremellodendropsidaceae': 1,\n", + " 'Hexanchiformes': 2,\n", + " 'Massospora': 0,\n", + " 'Cyclostomatida': 6,\n", + " 'Triblidiales': 1,\n", + " 'Callipodida': 4,\n", + " 'Strepsiptera': 4,\n", + " 'Chytridiales': 1,\n", + " 'Gonorynchiformes': 3,\n", + " 'Chloranthales': 1,\n", + " 'Ceratodontiformes': 3,\n", + " 'Tetrasporales': 2,\n", + " 'Pilobolaceae': 1,\n", + " 'Anthocerotales': 1,\n", + " 'Porocephalida': 2,\n", + " 'Macrodasyida': 7,\n", + " 'Lobotiformes': 3,\n", + " 'Gadilida': 2,\n", + " 'Buxbaumiales': 1,\n", + " 'Isocrinida': 3,\n", + " 'Isobryales': 4,\n", + " 'Persiculida': 2,\n", + " 'Dentaliida': 7,\n", + " 'Ceratophyllales': 1,\n", + " 'Myriangiales': 2,\n", + " 'Pyrosomatida': 1,\n", + " 'Sceptrulophora': 4,\n", + " 'Euechinoidea': 1,\n", + " 'Gordioidea': 2,\n", + " 'Parachela': 4,\n", + " 'Priapulomorpha': 2,\n", + " 'Aphragmophora': 1,\n", + " 'Leotiales': 2,\n", + " 'Branchiobdellida': 2,\n", + " 'Amborellales': 1,\n", + " 'Thelebolales': 1,\n", + " 'Cydippida': 6,\n", + " 'Chaetonotida': 2,\n", + " 'Oligacanthorhynchida': 1,\n", + " 'Homosclerophorida': 2,\n", + " 'Abrothallus': 0,\n", + " 'Stereopsis': 0,\n", + " 'Amylocorticiales': 1,\n", + " 'Picramniales': 1,\n", + " 'Enchytraeida': 1,\n", + " 'Polymixiiformes': 1,\n", + " 'Nemertodermatida': 2,\n", + " 'Coryneliales': 1,\n", + " 'Rhizophydiales': 1,\n", + " 'Erynia': 0,\n", + " 'Schistostegaceae': 1,\n", + " 'Cumacea': 6,\n", + " 'Berberidopsidales': 2,\n", + " 'Dendrocerotales': 1,\n", + " 'Dothideales': 3,\n", + " 'Geminibasidiaceae': 2,\n", + " 'Leptodontaceae': 1,\n", + " 'Echinorhynchida': 3,\n", + " 'Batrachospermales': 2,\n", + " 'Glomerida': 2,\n", + " 'Amphioxiformes': 1,\n", + " 'Septobasidiales': 1,\n", + " 'Monstrilloida': 1,\n", + " 'Thalassocalycida': 1,\n", + " 'Bivalvulida': 2,\n", + " 'Ateleopodiformes': 1,\n", + " 'Mantophasmatodea': 1,\n", + " 'Stylonematales': 1,\n", + " 'Mormonilloida': 1,\n", + " 'Chirodropida': 2,\n", + " 'Vampyromorpha': 1,\n", + " 'Prasiolales': 1,\n", + " 'Platygloeales': 2,\n", + " 'Moniliformida': 1,\n", + " 'Canuelloida': 2,\n", + " 'Amphidiscosida': 2,\n", + " 'Asaphida': 1,\n", + " 'Glaucocystales': 1,\n", + " 'Blastocladiales': 2,\n", + " 'Lichenoconiales': 1,\n", + " 'Normandina': 0,\n", + " 'Zoophthora': 0,\n", + " 'Polyxenida': 1,\n", + " 'Trypetheliales': 2,\n", + " 'Syncephalastraceae': 1,\n", + " 'Acrochaetiales': 1,\n", + " 'Treubiidae': 1,\n", + " 'Microthamniales': 0,\n", + " 'Palpigradi': 1,\n", + " 'Acrospermales': 1,\n", + " 'Magnaporthales': 2,\n", + " 'Bothrioplanida': 1,\n", + " 'Ahnfeltiales': 1,\n", + " 'Limnognathida': 1,\n", + " 'Endogonaceae': 1,\n", + " 'Archidiales': 1,\n", + " 'Tetramerocerata': 2,\n", + " 'Opilioacarida': 1,\n", + " 'Mortierellaceae': 1,\n", + " 'Wallemiales': 1,\n", + " 'Arguloida': 1,\n", + " 'Seisonacea': 1,\n", + " 'Echiniscoidea': 1,\n", + " 'Melanosporales': 1,\n", + " 'Microthyriales': 1,\n", + " 'Siphonophorida': 2,\n", + " 'Eryniopsis': 0,\n", + " 'Malasseziales': 1,\n", + " 'Schizosaccharomycetales': 1,\n", + " 'Microstromatales': 0,\n", + " 'Pyramimonadophyceae': 0,\n", + " 'Glomus': 0,\n", + " 'Doliolida': 1,\n", + " 'Acrosymphytales': 2,\n", + " 'Xanthopyreniaceae': 1,\n", + " 'Halicryptomorpha': 1,\n", + " 'Agyriales': 1,\n", + " 'Jobellisiaceae': 1,\n", + " 'Heterogastridiales': 1,\n", + " 'Rhodogorgonales': 1,\n", + " 'Platycopina': 1,\n", + " 'Coelacanthiformes': 1,\n", + " 'Polystilifera': 3,\n", + " 'Ophioleucida': 1,\n", + " 'Nectiopoda': 2,\n", + " 'Dendrogastrida': 2,\n", + " 'Leptostraca': 1,\n", + " 'Cunninghamellaceae': 3,\n", + " 'Lichida': 1,\n", + " 'Balliales': 1,\n", + " 'Trichosphaeriales': 1,\n", + " 'Entwisleiales': 1,\n", + " 'Meliolales': 1,\n", + " 'Prasinococcales': 1,\n", + " 'Klebsormidiales': 1,\n", + " 'Pandora': 0,\n", + " 'Myzostomida': 1,\n", + " 'Glaucosphaerales': 1,\n", + " 'Diversispora': 0,\n", + " 'Ibliformes': 1,\n", + " 'Platycopioida': 1,\n", + " 'Rhodochaetales': 1,\n", + " 'Redlichiida': 2,\n", + " 'Phacopida': 3,\n", + " 'Rhizophagus': 0,\n", + " 'Tritirachiales': 1,\n", + " 'Sebdeniales': 1,\n", + " 'Multivalvulida': 1,\n", + " 'Stylephoriformes': 1,\n", + " 'Zoraptera': 1,\n", + " 'Symbiida': 1,\n", + " 'Coleochaetales': 1,\n", + " 'Arthrotardigrada': 1,\n", + " 'Sporidiobolales': 0,\n", + " 'Tilletiales': 1,\n", + " 'Bursovaginoidea': 1,\n", + " 'Chaetodermatida': 2,\n", + " 'Mycotyphaceae': 1,\n", + " 'Tryblidiida': 1,\n", + " 'Cryptophialida': 1,\n", + " 'Chlorodendrales': 1,\n", + " 'Mesostigmatales': 1,\n", + " 'Geosiphon': 0,\n", + " 'Misophrioida': 1,\n", + " 'Scutellospora': 0,\n", + " 'Sporodiniella': 0,\n", + " 'Gnosonesimidae': 1,\n", + " 'Corynexochida': 1,\n", + " 'Hypnobryales': 1,\n", + " 'Redeckera': 0,\n", + " 'Oedogoniales': 0,\n", + " 'Lepidogalaxiiformes': 1,\n", + " 'Peripodida': 1,\n", + " 'Thoreales': 1,\n", + " 'Passeriformes': 72,\n", + " 'Columbiformes': 1,\n", + " 'Anseriformes': 3,\n", + " 'Accipitriformes': 3,\n", + " 'Nudibranchia': 16,\n", + " 'Adapedonta': 1,\n", + " 'Charadriiformes': 11,\n", + " 'Pelecaniformes': 4,\n", + " 'Piciformes': 4,\n", + " 'Sphenisciformes': 1,\n", + " 'Mytilida': 1,\n", + " 'Suliformes': 4,\n", + " 'Gruiformes': 3,\n", + " 'Scolopendromorpha': 1,\n", + " 'Rhodellales': 1,\n", + " 'Carnivora': 10,\n", + " 'Primates': 3,\n", + " 'Phoenicopteriformes': 1,\n", + " 'Strigiformes': 2,\n", + " 'Chiroptera': 4,\n", + " 'Artiodactyla': 12,\n", + " 'Ciconiiformes': 1,\n", + " 'Galliformes': 5,\n", + " 'Lagomorpha': 2,\n", + " 'Cuculiformes': 1,\n", + " 'Coraciiformes': 4,\n", + " 'Stylommatophora': 20,\n", + " 'Colaconematales': 1,\n", + " 'Venerida': 3,\n", + " 'Pectinida': 2,\n", + " 'Psittaciformes': 4,\n", + " 'Rodentia': 11,\n", + " 'Camarodonta': 2,\n", + " 'Procellariiformes': 2,\n", + " 'Forcipulatida': 1,\n", + " 'Caprimulgiformes': 5,\n", + " 'Marchantiales': 3,\n", + " 'Galbuliformes': 1,\n", + " 'Eulipotyphla': 3,\n", + " 'Myida': 3,\n", + " 'Falconiformes': 1,\n", + " 'Perissodactyla': 3,\n", + " 'Pilosa': 3,\n", + " 'Lecideales': 1,\n", + " 'Podicipediformes': 1,\n", + " 'Phaeotrichales': 1,\n", + " 'Scorpaeniformes': 3,\n", + " 'Ostreida': 1,\n", + " 'Sepiida': 1,\n", + " 'Caliciales': 1,\n", + " 'Trogoniformes': 1,\n", + " 'Cyrtocrinida': 1,\n", + " 'Dimargaritaceae': 1,\n", + " 'Cingulata': 1,\n", + " 'Casuariiformes': 1,\n", + " 'Diprotodontia': 5,\n", + " 'Rhynchocephalia': 1,\n", + " 'Endeostigmata': 1,\n", + " 'Jahnulales': 1,\n", + " 'Filospermoidea': 1,\n", + " 'Otidiformes': 1,\n", + " 'Cathartiformes': 1,\n", + " 'Spirulida': 1,\n", + " 'Bucerotiformes': 4,\n", + " 'Opisthocomiformes': 1,\n", + " 'Gaviiformes': 1,\n", + " 'Agaricostilbales': 0,\n", + " 'Monotremata': 2,\n", + " 'Gasterosteiformes': 1,\n", + " 'Sabellida': 2,\n", + " 'Coliiformes': 1,\n", + " 'Phacidiales': 1,\n", + " 'Jungermanniales': 1,\n", + " 'Sirenia': 1,\n", + " 'Aplysiida': 1,\n", + " 'Spinulosida': 1,\n", + " 'Musophagiformes': 1,\n", + " 'Cardiida': 2,\n", + " 'Didelphimorphia': 1,\n", + " 'Systellommatophora': 1,\n", + " 'Unionida': 1,\n", + " 'Scutigeromorpha': 1,\n", + " 'Clypeasteroida': 2,\n", + " 'Anthoathecata': 1,\n", + " 'Siphonophorae': 1,\n", + " 'Cephalaspidea': 1,\n", + " 'Haplotaxida': 1,\n", + " 'Lunulariales': 1,\n", + " 'Valvatida': 3,\n", + " 'Hyracoidea': 1,\n", + " 'Proboscidea': 1,\n", + " 'Dermoptera': 1,\n", + " 'Struthioniformes': 1,\n", + " 'Craniata': 1,\n", + " 'Rhizocarpales': 1,\n", + " 'Hedwigiales': 1}" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "num_families_order" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "num_orders_class = {}\n", + "num_families_class = {}\n", + "num_genera_class = {}\n", + "num_species_class = {}\n", + "for clss in df_taxa['class'].unique():\n", + " temp = df_taxa.loc[df_taxa['class'] == clss]\n", + " num_orders_class[clss] = temp['order'].nunique()\n", + " num_families_class[clss] = temp['family'].nunique()\n", + " num_genera_class[clss] = temp['genus'].nunique()\n", + " num_species_class[clss] = temp['species'].nunique()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "num_classes_phylum = {}\n", + "num_orders_phylum = {}\n", + "num_families_phylum = {}\n", + "num_genera_phylum = {}\n", + "num_species_phylum = {}\n", + "for phylum in df_taxa.phylum.unique():\n", + " temp = df_taxa.loc[df_taxa.phylum == phylum]\n", + " num_classes_phylum[phylum] = temp['class'].nunique()\n", + " num_orders_phylum[phylum] = temp['order'].nunique()\n", + " num_families_phylum[phylum] = temp['family'].nunique()\n", + " num_genera_phylum[phylum] = temp['genus'].nunique()\n", + " num_species_phylum[phylum] = temp['species'].nunique()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "num_phyla_kingdom = {}\n", + "num_classes_kingdom = {}\n", + "num_orders_kingdom = {}\n", + "for kingdom in df_taxa.kingdom.unique():\n", + " temp = df_taxa.loc[df_taxa.kingdom == kingdom]\n", + " num_phyla_kingdom[kingdom] = temp.phylum.nunique()\n", + " num_classes_kingdom[kingdom] = temp['class'].nunique()\n", + " num_orders_kingdom[kingdom] = temp['order'].nunique()" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "num_species_genus = {}\n", + "for genus in df_taxa.genus.unique():\n", + " temp = df_taxa.loc[df_taxa.genus == genus]\n", + " num_species_genus[genus] = temp.species.nunique()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Quick pause to save all progress to csv before starting final long calculation, then we can just add the number of species in each genus at the end." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Compile list of dictionaries to make DataFrame with all data\n", + "\n", + "Format:\n", + "| top_taxon | rank | num_phyla | num_classes | num_orders | num_families | num_genera | num_species |\n", + "| ------ | ------ | ---- | ---- | ---- | ---- | ---- | ---- |\n", + "| Animalia | Kingdom | # phyla | # classes | # orders | # families | # genera | # species |\n", + "..." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "kingdom_counts = [num_phyla_kingdom, num_classes_kingdom, num_orders_kingdom, num_families_kingdom, \n", + " num_genera_kingdom, num_species_kingdom]\n", + "phylum_counts = [num_classes_phylum, num_orders_phylum, num_families_phylum, num_genera_phylum, num_species_phylum]\n", + "class_counts = [num_orders_class, num_families_class, num_genera_class, num_species_class]\n", + "order_counts = [num_families_order, num_genera_order, num_species_order]\n", + "family_counts = [num_genera_family, num_species_family]\n", + "genus_counts = [num_species_genus]" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "dict_list = [{\"kingdom\": kingdom_counts},\n", + " {\"phylum\": phylum_counts},\n", + " {\"class\": class_counts},\n", + " {\"order\": order_counts},\n", + " {\"family\": family_counts},\n", + " {\"genus\": genus_counts}]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Generate the first two columns of our desired DataFrame. Note that all taxa but `genus` start with `nan` so we will ignore that value --not in first iteration" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "top_taxon = []\n", + "ranks = []\n", + "#i = 1\n", + "for taxon in taxa[:6]:\n", + " vals = list(df_taxa[taxon].unique())\n", + " #if taxon == 'genus': # since genus is last in list\n", + " # i = 0\n", + " for val in vals: #[i:]:\n", + " top_taxon.append(val)\n", + " ranks.append(taxon)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "taxa_cols = ['num_phyla', 'num_classes', 'num_orders', 'num_families', 'num_genera', 'num_species']" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "taxa_counts_df = pd.DataFrame({\"top_taxon\": top_taxon, \"rank\": ranks})" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " top_taxon rank num_phyla num_classes num_orders \\\n", + "0 NaN kingdom 1 1 1 \n", + "1 Metazoa kingdom 1 1 1 \n", + "2 Archaeplastida kingdom 1 1 1 \n", + "3 Fungi kingdom 1 1 1 \n", + "4 Animalia kingdom 1 1 1 \n", + "... ... ... ... ... ... \n", + "96536 Kribia genus 1 1 1 \n", + "96537 Chilodonta genus 1 1 1 \n", + "96538 Epihippus genus 1 1 1 \n", + "96539 Ancistria genus 1 1 1 \n", + "96540 Exneria genus 1 1 1 \n", + "\n", + " num_families num_genera num_species \n", + "0 1 1 1 \n", + "1 1 1 1 \n", + "2 1 1 1 \n", + "3 1 1 1 \n", + "4 1 1 1 \n", + "... ... ... ... \n", + "96536 1 1 1 \n", + "96537 1 1 1 \n", + "96538 1 1 1 \n", + "96539 1 1 1 \n", + "96540 1 1 1 \n", + "\n", + "[96541 rows x 8 columns]" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Set all other columns to default value of 1 since lower level taxa will only belong to the one higher level taxon\n", + "taxa_counts_df[taxa_cols] = 1\n", + "taxa_counts_df" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nan 0\n", + "0\n", + "Metazoa 31\n", + "0\n", + "Archaeplastida 7\n", + "0\n", + "Fungi 11\n", + "0\n", + "Animalia 6\n", + "0\n", + "Plantae 5\n", + "0\n", + "nan 0\n", + "1\n", + "Metazoa 61\n", + "1\n", + "Archaeplastida 22\n", + "1\n", + "Fungi 36\n", + "1\n", + "Animalia 27\n", + "1\n", + "Plantae 14\n", + "1\n", + "nan 0\n", + "2\n", + "Metazoa 355\n", + "2\n", + "Archaeplastida 176\n", + "2\n", + "Fungi 152\n", + "2\n", + "Animalia 160\n", + "2\n", + "Plantae 85\n", + "2\n", + "nan 0\n", + "3\n", + "Metazoa 4272\n", + "3\n", + "Archaeplastida 719\n", + "3\n", + "Fungi 468\n", + "3\n", + "Animalia 1077\n", + "3\n", + "Plantae 286\n", + "3\n", + "nan 0\n", + "4\n", + "Metazoa 39686\n", + "4\n", + "Archaeplastida 10182\n", + "4\n", + "Fungi 2019\n", + "4\n", + "Animalia 6225\n", + "4\n", + "Plantae 1702\n", + "4\n", + "nan 0\n", + "5\n", + "Metazoa 74323\n", + "5\n", + "Archaeplastida 33054\n", + "5\n", + "Fungi 7713\n", + "5\n", + "Animalia 12476\n", + "5\n", + "Plantae 2499\n", + "5\n" + ] + } + ], + "source": [ + "marker = 0\n", + "for king_dict in kingdom_counts:\n", + " for key, value in king_dict.items():\n", + " # key = higher taxon, value = num of lower taxa in it\n", + " print(key, value)\n", + " print(marker)\n", + " taxa_counts_df.loc[(taxa_counts_df['top_taxon'] == key) & (taxa_counts_df['rank'] == 'kingdom'), taxa_cols[marker]] = value\n", + " marker += 1" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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top_taxonranknum_phylanum_classesnum_ordersnum_familiesnum_generanum_species
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3Fungikingdom113615246820197713
4Animaliakingdom6271601077622512476
5Plantaekingdom5148528617022499
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964Reduviidaefamily11113473
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" + ], + "text/plain": [ + " top_taxon rank num_phyla num_classes num_orders \\\n", + "960 NaN family 1 1 1 \n", + "961 Oenosandridae family 1 1 1 \n", + "962 Rutaceae family 1 1 1 \n", + "963 Limnephilidae family 1 1 1 \n", + "964 Reduviidae family 1 1 1 \n", + "... ... ... ... ... ... \n", + "6621 Hedwigiaceae family 1 1 1 \n", + "6622 Jasmineiricolidae family 1 1 1 \n", + "6623 Cunninghamella family 1 1 1 \n", + "6624 Eremobelbidae family 1 1 1 \n", + "6625 Rhopalomeniidae family 1 1 1 \n", + "\n", + " num_families num_genera num_species \n", + "960 1 1 1 \n", + "961 1 1 4 \n", + "962 1 104 618 \n", + "963 1 58 223 \n", + "964 1 34 73 \n", + "... ... ... ... \n", + "6621 1 1 1 \n", + "6622 1 1 1 \n", + "6623 1 0 0 \n", + "6624 1 1 1 \n", + "6625 1 1 1 \n", + "\n", + "[5666 rows x 8 columns]" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "taxa_counts_df.loc[taxa_counts_df['rank'] == 'family']" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [], + "source": [ + "marker = 5\n", + "for genus_dict in genus_counts:\n", + " for key, value in genus_dict.items():\n", + " # key = higher taxon, value = num of lower taxa in it\n", + " taxa_counts_df.loc[(taxa_counts_df['top_taxon'] == key) & (taxa_counts_df['rank'] == 'genus'), taxa_cols[marker]] = value\n", + " marker += 1" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " top_taxon rank num_phyla num_classes num_orders num_families \\\n", + "6626 Manfreda genus 1 1 1 1 \n", + "6627 Discophlebia genus 1 1 1 1 \n", + "6628 Melicope genus 1 1 1 1 \n", + "6629 Limnephilus genus 1 1 1 1 \n", + "6630 NaN genus 1 1 1 1 \n", + "... ... ... ... ... ... ... \n", + "96536 Kribia genus 1 1 1 1 \n", + "96537 Chilodonta genus 1 1 1 1 \n", + "96538 Epihippus genus 1 1 1 1 \n", + "96539 Ancistria genus 1 1 1 1 \n", + "96540 Exneria genus 1 1 1 1 \n", + "\n", + " num_genera num_species \n", + "6626 1 3 \n", + "6627 1 5 \n", + "6628 1 39 \n", + "6629 1 81 \n", + "6630 1 1 \n", + "... ... ... \n", + "96536 1 1 \n", + "96537 1 1 \n", + "96538 1 1 \n", + "96539 1 1 \n", + "96540 1 1 \n", + "\n", + "[89915 rows x 8 columns]" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "taxa_counts_df.loc[taxa_counts_df['rank'] == 'genus']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Save resulting DataFrame to CSV. Note that the number of species per genus did not finish." + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "taxa_counts_df.to_csv(\"../data/taxa_counts.csv\", index = False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Returning to our original DataFrame, we want to get some counts by source dataset." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# Add data_source column for easier slicing\n", + "df.loc[df['inat21_filename'].notna(), 'data_source'] = 'iNat21'\n", + "df.loc[df['bioscan_filename'].notna(), 'data_source'] = 'BIOSCAN'\n", + "df.loc[df['eol_content_id'].notna(), 'data_source'] = 'EOL'" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "518118" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.loc[df['data_source'] == 'EOL', 'common'].nunique()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "9941" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.loc[df['data_source'] == 'iNat21', 'common'].nunique()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "10635" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.loc[df['data_source'] == 'BIOSCAN', 'common'].nunique()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "viz", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +}