<jupyter_start><jupyter_text>Monoecious Hydrilla *Hydrilla verticillata [monoecious]*---<jupyter_code>%load_ext autoreload
%autoreload 2
import sys

import numpy as np
import pandas as pd

import flbs_ais.nas as nas<jupyter_output><empty_output><jupyter_text>Database Species Search Results<jupyter_code>search_result = nas.species_search('Hydrilla', '')
search_string = nas.species_string(search_result)
print(search_string)<jupyter_output>speciesID: 6
itis_tsn: 38974
group: Plants
family: Hydrocharitaceae
genus: Hydrilla
species: verticillata
subspecies: 
variety: 
authority: (L.f.) Royle
common_name: hydrilla
native_exotic: Exotic
Fresh/Marine/Brackish: Freshwater

speciesID: 2942
itis_tsn: 38974
group: Plants
family: Hydrocharitaceae
genus: Hydrilla
species: verticillata [dioecious]
subspecies: 
variety: 
authority: (L. f.) Royle
common_name: dioecious hydrilla
native_exotic: Exotic
Fresh/Marine/Brackish: Freshwater

speciesID: 2943
itis_tsn: 38974
group: Plants
family: Hydrocharitaceae
genus: Hydrilla
species: verticillata [monoecious]
subspecies: 
variety: 
authority: (L. f.) Royle
common_name: monoecious hydrilla
native_exotic: Exotic
Fresh/Marine/Brackish: Freshwater<jupyter_text>--- API Query Dataframe for Monoecious Hydrilla<jupyter_code>api_key = ""
with open("../tmp/api_key.txt", 'r') as file:
    api_key = file.readline()
api_df = nas.getdf(2943, keep_columns=None, limit=-1, api_key=api_key)
print(f"Results: {len(api_df)}")
api_df.head()<jupyter_output>Results: 672<jupyter_text>--- Most Common References for API Query Dataframe<jupyter_code>api_ref_count = nas.ref_counts(api_df)
print(nas.ref_string(api_ref_count, limit=5))<jupyter_output>--------
Most common reference 1

Total Occurrences:  85
--------

--------
Most common reference 2

Source number:      1
Title:              Economical and Environmental Impacts of N.C. Aquatic Weed Infestations.
Author:             North Carolina Division of Water Resources.
Publisher:          North Carolina Department of Environment, Health, and Natural Resources.
Publisher Location: Raleigh, NC
Year:               1996
Reference Type:     Book

Total Occurrences:  60
--------

--------
Most common reference 3

Source number:      1
Title:              Calflora
Author:             <NAME>., <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>.
Publisher:          
Publisher Location: Berkeley, CA
Year:               2019
Reference Type:     Database

Total Occurrences:  57
--------

--------
Most common reference 4

Source number:      1
Title:              Joint Aquatic Invasive Species Survey, 2010
Author:             Central Hardwoods Invasive Plant Network.
Publish[...]<jupyter_text>--- CSV File Dataframe for Monoecious Hydrilla<jupyter_code>csv_df = nas.process_csv_df("../tmp/NAS-Data-MonoeciousHydrilla.csv")
print(f"Results: {len(csv_df)}")
csv_df.head()<jupyter_output>Results: 687<jupyter_text>--- Most Common References for CSV File Dataframe<jupyter_code>csv_ref_count = nas.ref_counts(csv_df)
print(nas.ref_string(csv_ref_count, limit=20))<jupyter_output>--------
Most common reference 1

Total Occurrences:  86
--------

--------
Most common reference 2

Source number:      1
Title:              Economical and Environmental Impacts of N.C. Aquatic Weed Infestations.
Author:             North Carolina Division of Water Resources.
Publisher:          North Carolina Department of Environment, Health, and Natural Resources.
Publisher Location: Raleigh, NC
Year:               1996
Reference Type:     Book

Total Occurrences:  73
--------

--------
Most common reference 3

Source number:      1
Title:              Calflora
Author:             <NAME>., <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>.
Publisher:          nan
Publisher Location: Berkeley, CA
Year:               2019
Reference Type:     Database

Total Occurrences:  57
--------

--------
Most common reference 4

Source number:      1
Title:              Joint Aquatic Invasive Species Survey, 2010
Author:             Central Hardwoods Invasive Plant Network.
Publ[...]
{'fraction_non_alphanumeric': 0.11124876114965312, 'fraction_numerical': 0.02205153617443013, 'mean_word_length': 3.4855555555555555, 'pattern_counts': {'":': 0, '<': 32, '<?xml version=': 0, '>': 32, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '6', 'dir': 'jupyter-structured-clean-dedup', 'id': '499304', 'license': 'MIT', 'n_tokens_mistral': 1399, 'n_tokens_neox': 1267, 'n_words': 365, 'path': 'notebooks/MonoeciousHydrilla.ipynb', 'repo_name': 'randywf/flbs-invasive-species', 'size': '4082'}