8 Data Portal

Download the Data Used in the Report’s Figures

Published

Sep 10, 2024 at 17:47 UTC

8.1 Data Overview

The data used in this web-book is derived from federal, state, commercial, and local sources, as well as direct communications with utilities and state program managers. More information about data sources can be found on the methods page of this web-book.

8.2 Download Individual Tables

Individual tables can be downloaded here as text files (CSV, comma-separated values). Once downloaded to your local machine, these files can be opened graphically using Microsoft Excel, or programmatically using R or Python.

Capacity

capacity_wide_description = metadata.resources[0].description;
capacity_wide_raw = FileAttachment("data/final_data/capacity.csv").csv({typed: true});

capacity_wide = tidy(capacity_wide_raw,
                  filter((d) => d.year < 2020))

capacity_wide_path = metadata.resources[0].path;
capacity_wide_metadata = metadata.resources[0].schema.fields;


viewof capacity_input = Inputs.select(new Map([
                ["Capacity Metadata", capacity_wide_metadata], 
                ["Capacity", capacity_wide]]), 
              {value: capacity_wide_metadata, label: "Preview:"}
              );

Inputs.table(capacity_input);

Download

button(capacity_wide_metadata, 'capacity_metadata.csv', `Capacity Metadata`)

button(capacity_wide, `capacity.csv`, `Capacity`)

Net Generation

net_generation_wide_description = metadata.resources[2].description
net_generation_wide_raw = FileAttachment("data/final_data/generation.csv").csv({typed: true});

net_generation_wide = tidy(net_generation_wide_raw,
                  filter((d) => d.year < 2020))

net_generation_wide_path = metadata.resources[2].path
net_generation_wide_metadata = metadata.resources[2].schema.fields

viewof generation_input = Inputs.select(new Map([["Generation Metadata", net_generation_wide_metadata], 
              ["Generation", net_generation_wide]]), 
              {value: net_generation_wide_metadata, label: "Preview:"}
              );
Inputs.table(generation_input);

Download

button(net_generation_wide_metadata, 'net_generation_metadata.csv', `Generation Metadata`)

button(net_generation_wide, `generation.csv`, `Net Generation`)

Consumption and Sales

consumption_wide_description = metadata.resources[4].description
consumption_wide_raw = FileAttachment("data/final_data/consumption.csv").csv({typed: true});

consumption_wide = tidy(consumption_wide_raw,
                  filter((d) => d.year < 2020))

consumption_wide_path = metadata.resources[4].path
consumption_wide_metadata = metadata.resources[4].schema.fields

viewof consumption_input = Inputs.select(new Map([["Consumption Metadata", consumption_wide_metadata], 
              ["Consumption", consumption_wide]]), 
              {value: consumption_wide_metadata, label: "Preview:"}
              );
Inputs.table(consumption_input);

Download

button(consumption_wide_metadata, 'consumption_wide_metadata.csv', `Consumption Metadata`)

button(consumption_wide, `consumption_wide.csv`, `Consumption`)

Prices

prices_description = metadata.resources[6].description;
prices_raw = FileAttachment("data/final_data/prices.csv").csv({typed: true});

prices = tidy(prices_raw,
            filter((d) => d.year < 2020))

prices_path = metadata.resources[6].path;
prices_metadata = metadata.resources[6].schema.fields;


viewof prices_input = Inputs.select(new Map([["Prices Metadata", prices_metadata], 
              ["Prices", prices]]), 
              {value: prices_metadata, label: "Preview:"}
              );

Inputs.table(prices_input);

Download

button(prices_metadata, `prices_metadata.csv`, `Metadata`);

button(prices, `prices.csv`, `Prices`);

Population-Weighted Average Prices

weighted_prices_description = metadata.resources[7].description;
weighted_prices_raw = FileAttachment("data/final_data/weighted_prices.csv").csv({typed: true});

weighted_prices = tidy(weighted_prices_raw,
                    filter((d) => d.year < 2020))

weighted_prices_path = metadata.resources[7].path;
weighted_prices_metadata = metadata.resources[7].schema.fields;

viewof weighted_prices_input = Inputs.select(new Map([["Weighted Prices Metadata", weighted_prices_metadata], 
              ["Weighted Prices", weighted_prices]]), 
              {value: weighted_prices_metadata, label: "Preview:"}
              );

Inputs.table(weighted_prices_input);

Download

button(weighted_prices_metadata, `weighted_prices_metadata.csv`, `Metadata`);

button(weighted_prices, `weighted_prices.csv`, `Weighted Prices`)

stdlib = require("@observablehq/stdlib")
d3 = require("d3@7")
import {tidy, groupBy, rename, summarize, sum, mutate, select, n, nDistinct, mean, filter, pivotWider, pivotLonger, leftJoin, slice} from "@pbeshai/tidyjs"

// load metadata
metadata = FileAttachment("data/final_data/metadata.json").json();

// download button function
button = (data, filename = 'data.csv', displayname) => {
  const downloadData = new Blob([d3.csvFormat(data)], { type: "text/csv" });

  const size = (downloadData.size / 1024).toFixed(1);
  const button = DOM.download(
    downloadData,
    filename,
    `${displayname} (${size} KB)`
  );
  return button;
}

db = FileAttachment("data/working/aetr.db").sqlite()

viewof dbTable = Inputs.select((await db.describe()).value.map(d => d.name), 
                    { label: "" })

database = db.query(`SELECT * FROM ${dbTable}`)


Inputs.table(database)

db_button = (database, filename = 'data.csv') => {
  const downloadData = new Blob([d3.csvFormat(database)], { type: "text/csv" });

  const size = (downloadData.size / 1024).toFixed(1);
  const button = DOM.download(
    downloadData,
    filename,
    `Download ${filename} (${size} KB)`
  );
  return button;
}

db_button(database, `${dbTable}`)