Datasets:
| # -*- coding: utf-8 -*- | |
| """DurhamTrees | |
| Automatically generated by Colaboratory. | |
| Original file is located at | |
| https://colab.research.google.com/drive/1Hvt3Y131OjTl7oGQGS55S_v7-aYu1Yj8 | |
| """ | |
| from datasets import DatasetBuilder, DownloadManager, DatasetInfo, SplitGenerator, Split | |
| from datasets.features import Features, Value, ClassLabel | |
| import pandas as pd | |
| import geopandas as gpd | |
| import matplotlib.pyplot as plt | |
| import csv | |
| import json | |
| import os | |
| from typing import List | |
| import datasets | |
| class DurhamTrees(DatasetBuilder): | |
| _URLS = { | |
| "csv": "https://drive.google.com/uc?export=download&id=18HmgMbtbntWsvAySoZr4nV1KNu-i7GCy", | |
| "geojson": "https://drive.google.com/uc?export=download&id=1jpFVanNGy7L5tVO-Z_nltbBXKvrcAoDo" | |
| } | |
| VERSION = datasets.Version("1.0.0") | |
| def _info(self): | |
| # Specifies the dataset's features | |
| return DatasetInfo( | |
| description="This dataset contains information about tree planting sites from CSV and GeoJSON files.", | |
| features=Features({ | |
| "geometry": Value("string"), # Geometry feature, usually spatial data (GeoJSON format) | |
| "OBJECTID": Value("int64"), # Unique identifier for each record | |
| "streetaddress": Value("string"), # Street address of the tree planting site | |
| "city": Value("string"), # City where the tree planting site is located | |
| "zipcode": Value("int64"), # Zip code of the tree planting site | |
| "facilityid": Value("int64"), # Identifier for the facility | |
| "present": Value("string"), # Presence status, assumed to be string | |
| "genus": Value("string"), # Genus of the tree | |
| "species": Value("string"), # Species of the tree | |
| "commonname": Value("string"), # Common name of the tree | |
| "diameterin": Value("float64"), # Diameter in inches | |
| "heightft": Value("float64"), # Height in feet (changed to "float64") | |
| "condition": Value("string"), # Condition of the tree | |
| "contractwork": Value("string"), # Contract work information | |
| "neighborhood": Value("string"), # Neighborhood where the tree is located | |
| "program": Value("string"), # Program under which the tree was planted | |
| "plantingw": Value("string"), # Width available for planting | |
| "plantingcond": Value("string"), # Planting condition | |
| "underpwerlins": Value("string"), # Whether the tree is under power lines | |
| "GlobalID": Value("string"), # Global identifier | |
| "created_user": Value("string"), # User who created the record | |
| "last_edited_user": Value("string"), # User who last edited the record | |
| "isoprene": Value("float64"), # Isoprene emission rate | |
| "monoterpene": Value("float64"), | |
| "coremoved_ozperyr": Value("float64"), # Carbon monoxide removed, in ounces per year | |
| "coremoved_dolperyr": Value("float64"), # Monetary value of carbon monoxide removal per year | |
| "o3removed_ozperyr": Value("float64"), # Ozone removed, in ounces per year | |
| "o3removed_dolperyr": Value("float64"), # Monetary value of ozone removal per year | |
| "no2removed_ozperyr": Value("float64"), # Nitrogen dioxide removed, in ounces per year | |
| "no2removed_dolperyr": Value("float64"), # Monetary value of nitrogen dioxide removal per year | |
| "so2removed_ozperyr": Value("float64"), # Sulfur dioxide removed, in ounces per year | |
| "so2removed_dolperyr": Value("float64"), # Monetary value of sulfur dioxide removal per year | |
| "pm10removed_ozperyr": Value("float64"), # Particulate matter (10 micrometers or less) removed, in ounces per year | |
| "pm10removed_dolperyr": Value("float64"), # Monetary value of particulate matter removal per year | |
| "pm25removed_ozperyr": Value("float64"), # Particulate matter (2.5 micrometers or less) removed, in ounces per year | |
| "o2production_lbperyr": Value("float64"), # Oxygen production, in pounds per year | |
| "replacevalue_dol": Value("float64"), # Replacement value in dollars | |
| "carbonstorage_lb": Value("float64"), # Carbon storage, in pounds | |
| "carbonstorage_dol": Value("float64"), # Monetary value of carbon storage | |
| "grosscarseq_lbperyr": Value("float64"), # Gross carbon sequestration, in pounds per year | |
| "X": Value("float64"), # X coordinate (longitude if geographic) | |
| "Y": Value("float64"), # Y coordinate (latitude if geographic) | |
| }), | |
| supervised_keys=None, | |
| homepage="https://github.com/AuraMa111?tab=repositories", | |
| citation="Citation for the dataset", | |
| ) | |
| def _split_generators(self, dl_manager: DownloadManager): | |
| urls_to_download = self._URLS # This should now work as _URLS is defined | |
| downloaded_files = dl_manager.download_and_extract(urls_to_download) | |
| return [ | |
| SplitGenerator(name=Split.TRAIN, gen_kwargs={ | |
| "csv_path": downloaded_files["csv"], | |
| "geojson_path": downloaded_files["geojson"] | |
| }), | |
| # If you have additional splits, define them here | |
| ] | |
| def _generate_examples(self, csv_path, geojson_path): | |
| # Log the information about the CSV file being processed | |
| # Load the CSV data into a pandas DataFrame | |
| csv_data = pd.read_csv(csv_path) | |
| # Load the GeoJSON data into a GeoDataFrame | |
| geojson_data = gpd.read_file(geojson_path) | |
| # Merge the CSV data with the GeoJSON data on the 'OBJECTID' column | |
| merged_data = geojson_data.merge(csv_data, on='OBJECTID') | |
| # Drop columns with suffix '_y' that might have been created during the merge | |
| merged_data.drop(columns=[col for col in merged_data if col.endswith('_y')], inplace=True) | |
| # Rename columns to remove suffix '_x' | |
| merged_data.rename(columns=lambda x: x.rstrip('_x'), inplace=True) | |
| # Select the desired columns | |
| columns_to_extract = [ "geometry", # Geometry feature, usually spatial data (GeoJSON format) | |
| "OBJECTID", # Unique identifier for each record | |
| "streetaddress", # Street address of the tree planting site | |
| "city", # City where the tree planting site is located | |
| "zipcode", # Zip code of the tree planting site (changed to string) | |
| "facilityid", # Identifier for the facility | |
| "present", # Presence status, assumed to be string | |
| "genus", # Genus of the tree | |
| "species", # Species of the tree | |
| "commonname", # Common name of the tree | |
| "diameterin", # Diameter in inches | |
| "heightft", # Height in feet (changed to "float64") | |
| "condition", # Condition of the tree | |
| "contractwork", # Contract work information | |
| "neighborhood", # Neighborhood where the tree is located | |
| "program", # Program under which the tree was planted | |
| "plantingw", # Width available for planting | |
| "plantingcond", # Planting condition | |
| "underpwerlins", # Whether the tree is under power lines | |
| "GlobalID", # Global identifier | |
| "created_user", # User who created the record | |
| "last_edited_user", # User who last edited the record | |
| "isoprene", # Isoprene emission rate | |
| "monoterpene", | |
| "coremoved_ozperyr", # Carbon monoxide removed, in ounces per year | |
| "coremoved_dolperyr", # Monetary value of carbon monoxide removal per year | |
| "o3removed_ozperyr", # Ozone removed, in ounces per year | |
| "o3removed_dolperyr", # Monetary value of ozone removal per year | |
| "no2removed_ozperyr", # Nitrogen dioxide removed, in ounces per year | |
| "no2removed_dolperyr", # Monetary value of nitrogen dioxide removal per year | |
| "so2removed_ozperyr", # Sulfur dioxide removed, in ounces per year | |
| "so2removed_dolperyr", # Monetary value of sulfur dioxide removal per year | |
| "pm10removed_ozperyr", # Particulate matter (10 micrometers or less) removed, in ounces per year | |
| "pm10removed_dolperyr", # Monetary value of particulate matter removal per year | |
| "pm25removed_ozperyr", # Particulate matter (2.5 micrometers or less) removed, in ounces per year | |
| "o2production_lbperyr", # Oxygen production, in pounds per year | |
| "replacevalue_dol", # Replacement value in dollars | |
| "carbonstorage_lb", # Carbon storage, in pounds | |
| "carbonstorage_dol", # Monetary value of carbon storage | |
| "grosscarseq_lbperyr", # Gross carbon sequestration, in pounds per year | |
| "X", # X coordinate (longitude if geographic) | |
| "Y"] | |
| # Create the final DataFrame with the selected columns | |
| df = merged_data[columns_to_extract] | |
| # Iterate over each row in the DataFrame and yield it | |
| for index, row in df.iterrows(): | |
| # Convert the row to a dictionary, it's more convenient for yielding | |
| yield index, row.to_dict() | |