data.qmd

---
title: "Data Portal"
subtitle: "Download the Data Used in the Report's Figures"
---

```{r, echo=FALSE,warning=FALSE,message=FALSE}

# Function to make space regardless of execution format
# To use: write `r space() outside of a code block
# Modify globally at ./scripts/inline_functions/space.R
source("scripts/R/space.R")

```

`r space(br="", vspace="-3em")`

::: {.content-visible when-format="pdf"}
## Data Overview
The data used in this report 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 web-book version of this report at:

https://acep-uaf.github.io/aetr-web-book-2024/methods.html


## Download Individual Tables
To download the data itself, please visit this report's corresponding web-book at:  

 https://acep-uaf.github.io/aetr-web-book-2024/data.html

:::


::: {.content-visible when-format="html"}
## 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](https://acep-uaf.github.io/ak-energy-statistics-2011_2021/) can be found on the [methods page](./methods.html) of this web-book.

## 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
`{ojs} capacity_wide_description`

```{ojs}
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);

```

:::: {.columns}
::: {.column width="20%"}
#### Download
#### Download
:::
::: {.column width="80%"}
```{ojs}
button(capacity_wide_metadata, 'capacity_metadata.csv', `Capacity Metadata`)
button(capacity_wide, `capacity.csv`, `Capacity`)
```
:::
:::

<br>
<br>

### Net Generation
`{ojs} net_generation_wide_description `

```{ojs}
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);

```

:::: {.columns}
::: {.column width="20%"}
#### Download
#### Download
:::
::: {.column width="80%"}
```{ojs}
button(net_generation_wide_metadata, 'net_generation_metadata.csv', `Generation Metadata`)
button(net_generation_wide, `generation.csv`, `Net Generation`)
```
:::
:::

<br>
<br>

### Consumption and Sales
`{ojs} consumption_wide_description`

```{ojs}
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);

```

:::: {.columns}
::: {.column width="20%"}
#### Download
#### Download
:::
::: {.column width="80%"}
```{ojs}
button(consumption_wide_metadata, 'consumption_wide_metadata.csv', `Consumption Metadata`)
button(consumption_wide, `consumption_wide.csv`, `Consumption`)

```
:::
:::

<br>
<br>


### Prices
`{ojs} prices_description `

```{ojs}
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);

```

:::: {.columns}
::: {.column width="20%"}
#### Download
#### Download
:::
::: {.column width="80%"}
```{ojs}
button(prices_metadata, `prices_metadata.csv`, `Metadata`);
button(prices, `prices.csv`, `Prices`);
``` 
:::
:::

<br>
<br>

### Population-Weighted Average Prices
`{ojs} weighted_prices_description `

```{ojs}
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);

```

:::: {.columns}
::: {.column width="20%"}
#### Download
#### Download
:::
::: {.column width="80%"}
```{ojs}
button(weighted_prices_metadata, `weighted_prices_metadata.csv`, `Metadata`);
button(weighted_prices, `weighted_prices.csv`, `Weighted Prices`)
```
:::
:::




```{ojs}
// load libraries
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();

```

```{ojs}
// 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;
}

```


<br>
<br>
<br>

```{ojs}
//| eval: false
// DEPRECATED
// THIS CHUNK DOES NOT RUN (eval: false)

// fancy dropdown database viewing tool

// connect to database
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}`)
```
:::