Import Tutorial
Many government agencies distribute official data and statistics in workbooks. SheetJS libraries help translate these files to useful information.
The goal of this example is to process Federal Student Aid Portfolio data from a XLS worksheet. We will download and parse a workbook from the US Department of Education. Once the raw data is parsed, we will extract the total outstanding dollar amount and display the data in a table.
The "Live Demo" section includes a working demo in this page! "Run the Demo Locally" shows how to run the workflow in iOS / Android apps, desktop apps, NodeJS scripts and other environments.
The following sequence diagram shows the process:
Download File
The raw data is available in a XLS workbook1. It has been mirrored at https://docs.sheetjs.com/PortfolioSummary.xls
This official dataset is distributed in XLS workbooks.
SheetJS supports a number of legacy and modern formats, ensuring that historical data is not lost in the sands of time.
Downloading the file is straightforward with fetch
:
const url = "https://docs.sheetjs.com/PortfolioSummary.xls";
const file = await (await fetch(url)).arrayBuffer();
Code Explanation (click to show)
fetch
is a low-level API for downloading data from an endpoint. It separates
the network step from the response parsing step.
Network Step
fetch(url)
returns a Promise
representing the network request. The browser
will attempt to download data from the URL. If the network request succeeded,
the Promise
will "return" with a Response
object.
Using modern syntax, inside an async
function, code should await
the fetch:
const response = await fetch(url);
Checking Status Code
If the file is not available, the fetch
will still succeed.
The status code, stored in the status
property of the Response
object, is a
standard HTTP status code number. Code should check the result.
Typically servers will return status 404
"File not Found" if the file is not
available. A successful request should have status 200
"OK".
Extracting Data
Response#arrayBuffer
will pull the raw bytes into an ArrayBuffer
, an object
which can represent the file data. Like fetch
, the arrayBuffer
method
returns a Promise
that must be await
-ed:
const file = await response.arrayBuffer();
The Response
object has other useful methods. Response#json
will parse the
data with JSON.parse
, suitable for data from an API endpoint.
Production Use
Functions can test each part independently and report different errors:
async function get_file_from_endpoint(url) {
/* perform network request */
let response;
try {
response = await fetch(url);
} catch(e) {
/* network error */
throw new Error(`Network Error: ${e.message}`);
}
/* check status code */
if(response.status == 404) {
/* server 404 error -- file not found */
throw new Error("File not found");
}
if(response.status != 200) {
/* for most servers, a successful response will have status 200 */
throw new Error(`Server status ${response.status}: ${response.statusText}`);
}
/* get data */
let ab;
try {
ab = await response.arrayBuffer();
} catch(e) {
/* data error */
throw new Error(`Data Error: ${e.message}`);
}
return ab;
}
The file data is stored in an ArrayBuffer
.
Parse File
With the file data in hand, XLSX.read
2 parses the workbook:
const workbook = XLSX.read(file);
The workbook
object follows the "Common Spreadsheet Format"3, an in-memory
format for representing workbooks, worksheets, cells, and spreadsheet features.
Explore Dataset
Spreadsheets in the wild use many different inconsistent conventions.
To determine how to process the data, it is best to inspect the file first.
List Sheet Names
As explained in the "Workbook Object"4 section, the SheetNames
property is
a ordered list of the sheet names in the workbook.
The following live code block displays an ordered list of the sheet names:
function SheetJSheetNames() { const [names, setNames] = React.useState([]); React.useEffect(() => { (async() =>{ /* parse workbook */ const url = "https://docs.sheetjs.com/PortfolioSummary.xls"; const file = await (await fetch(url)).arrayBuffer(); const workbook = XLSX.read(file); /* display sheet names */ setNames(workbook.SheetNames); })(); }, []); return ( <> <b>Sheet Names</b><br/> <ol start={0}>{names.map(n => (<li>{n}</li>))}</ol> </> ) }
Inspect Worksheet Data
The Sheets
property of the workbook object5 is an object whose keys are
sheet names and whose values are sheet objects. For example, the first worksheet
is pulled by indexing SheetNames
and using the name to index Sheets
:
var first_sheet = workbook.Sheets[workbook.SheetNames[0]];
The actual worksheet object can be inspected directly6, but it is strongly recommended to use utility functions to present JS-friendly data structures.
Preview HTML
The sheet_to_html
utility function7 generates an HTML table from worksheet
objects. The following live example shows the first 20 rows of data in a table:
Live example (click to show)
SheetJS CE primarily focuses on data processing.
SheetJS Pro supports reading cell styles from files and generating styled HTML tables with colors, fonts, alignment and rich text.
function SheetJSHTMLView() { const [__html, setHTML] = React.useState(""); React.useEffect(() => { (async() =>{ /* parse workbook, limiting to 20 rows */ const url = "https://docs.sheetjs.com/PortfolioSummary.xls"; const workbook = XLSX.read(await (await fetch(url)).arrayBuffer(), {sheetRows:20}); /* get first worksheet */ const worksheet = workbook.Sheets[workbook.SheetNames[0]]; /* generate and display HTML */ const table = XLSX.utils.sheet_to_html(worksheet); setHTML(table); })(); }, []); return ( <div dangerouslySetInnerHTML={{__html}}/> ); }
The key points from looking at the table are:
- The data starts on row 7
- Rows 5 and 6 are the header rows, with merged cells for common titles
- For yearly data (2007-2012), columns A and B are merged
- For quarterly data (2013Q1 and later), column A stores the year. Cells may be merged vertically to span 4 quarters
Extract Data
Extract Raw Data
XLSX.utils.sheet_to_json
8 generates arrays of data from worksheet objects.
For a complex layout like this, it is easiest to generate an "array of arrays" where each row is an array of cell values. The screenshot shows rows 5-8:
In the array of arrays, row 5 has a number of gaps corresponding to empty cells and cells that are covered in the merge ranges:
// Row 5 -- the gaps correspond to cells with no content
[ , , "Direct Loans", , "Federal Family Education Loans (FFEL)", , "Perkins Loans", , "Total1" ]
Row 7 includes the data for FY2007:
// Row 7 -- column B is covered by the merge
[ 2007, , 106.8, 7, 401.9, 22.6, 8.2, 2.8, 516, 28.3 ]
XLSX.utils.sheet_to_json
will generate an array of arrays if the option
header: 1
is specified9:
const worksheet = workbook.Sheets[workbook.SheetNames[0]];
const raw_data = XLSX.utils.sheet_to_json(worksheet, {header: 1});
Fill Merged Blocks
Cells A13:A16
are merged:
The merged data only applies to the top-left cell (A13
). The array of arrays
will have holes in cells A14:A16
(written as null
):
// Row 13
[2013, "Q1", 508.7, 23.4, 444.9, 22.1, 8.2, 3, 961.9, 38.7]
// Row 14
[null, "Q2", 553, 24.1, 437, 21.6, 8.3, 3, 998.6, 38.9]
// Row 15
[null, "Q3", 569.2, 24.3, 429.5, 21.2, 8.2, 2.9, 1006.8, 38.7]
// Row 16
[null, "Q4", 609.1, 25.6, 423, 20.9, 8.1, 2.9, 1040.2, 39.6]
Live example (click to show)
function SheetJSAoAHoles() { const [rows, setRows] = React.useState([]); React.useEffect(() => { (async() =>{ /* parse workbook */ const url = "https://docs.sheetjs.com/PortfolioSummary.xls"; const workbook = XLSX.read(await (await fetch(url)).arrayBuffer()); /* get first worksheet */ const worksheet = workbook.Sheets[workbook.SheetNames[0]]; const raw_data = XLSX.utils.sheet_to_json(worksheet, {header:1}); /* pull Excel rows 13:16 (SheetJS 12:15) */ const rows_13_16 = raw_data.slice(12,16); /* display data */ setRows(rows_13_16); })(); }, []); return ( <pre>Rows 13:16{rows.map(r => "\n"+JSON.stringify(r))}</pre> ); }
The worksheet !merges
property10 includes every merge range in the sheet.
It is possible to loop through every merge block and fill cells, but in this
case it is easier to post-process the raw data:
let last_year = 0;
raw_data.forEach(r => last_year = r[0] = (r[0] != null ? r[0] : last_year));
JavaScript code can be extremely concise. The "Code Explanation" blocks explain the code in more detail.
Code Explanation (click to show)
Analyzing every row in the dataset
Array#forEach
takes a function and calls it for every element in the array.
Any modifications to objects affect the objects in the original array.
For example, this loop will print out the first column in the arrays:
raw_data.forEach(r => {
console.log(r);
});
Tracking the last value seen in a column
When looping over the array, Array#forEach
can modify variables outside of the
function body. For example, the following loop keeps track of the last value:
let last_value = null;
raw_data.forEach(r => {
if(r[0] != null) last_value = r[0];
});
Filling in data
Array#forEach
can mutate objects. The following code will assign the last
value to the first column if it is not specified:
let last_value = null;
raw_data.forEach(r => {
if(r[0] != null) last_value = r[0];
else if(r[0] == null && last_value != null) r[0] = last_value;
});
Simplifying the code
When r[0] == null
and last_value == null
, assigning r[0] = last_value
will
not affect the result in the actual data rows:
let last_value = null;
raw_data.forEach(r => {
if(r[0] != null) last_value = r[0];
else if(r[0] == null) r[0] = last_value;
});
For simple data rows, either r[0] == null
or r[0] != null
, so the if
block
can be rewritten as a ternary expression:
let last_value = null;
raw_data.forEach(r => {
(r[0] != null) ? (last_value = r[0]) : (r[0] = last_value);
});
Observing that r[0]
must equal last_value
, the inner statement can be
rewritten to compute the final value and assign to both variables:
let last_value = null;
raw_data.forEach(r => {
last_value = r[0] = (r[0] != null ? r[0] : last_value);
});
It is tempting to take advantage of implicit logical rules:
let last_value = null;
raw_data.forEach(r => {
last_value = r[0] = (r[0] || last_value);
});
This is strongly discouraged since the value 0
is false. The explicit null
test distinguishes null
and undefined
from 0
After post-processing, the rows now have proper year fields:
// Row 13
[2013, "Q1", 508.7, 23.4, 444.9, 22.1, 8.2, 3, 961.9, 38.7]
// Row 14
[2013, "Q2", 553, 24.1, 437, 21.6, 8.3, 3, 998.6, 38.9]
// Row 15
[2013, "Q3", 569.2, 24.3, 429.5, 21.2, 8.2, 2.9, 1006.8, 38.7]
// Row 16
[2013, "Q4", 609.1, 25.6, 423, 20.9, 8.1, 2.9, 1040.2, 39.6]
Live example (click to show)
function SheetJSAoAFilled() { const [rows, setRows] = React.useState([]); React.useEffect(() => { (async() =>{ /* parse workbook */ const url = "https://docs.sheetjs.com/PortfolioSummary.xls"; const workbook = XLSX.read(await (await fetch(url)).arrayBuffer()); /* get first worksheet */ const worksheet = workbook.Sheets[workbook.SheetNames[0]]; const raw_data = XLSX.utils.sheet_to_json(worksheet, {header:1}); /* fill years */ var last_year = 0; raw_data.forEach(r => last_year = r[0] = (r[0] != null ? r[0] : last_year)); /* pull Excel rows 13:16 (SheetJS 12:15) */ const rows_13_16 = raw_data.slice(12,16); /* display data */ setRows(rows_13_16); })(); }, []); return ( <pre>Rows 13:16{rows.map(r => "\n"+JSON.stringify(r))}</pre> ); }
Select Data Rows
At this point, each data row will have the year in column A
and dollar value
in column C
. The year will be between 2007 and 2024 and the value will be
positive. The following function tests a data row:
const is_valid_row = r =>
r[0] >= 2007 && r[0] <= 2024 // year (column A) is between 2007 and 2024
&& r[2] > 0; // dollar value (column C) is positive
Array#filter
, using the previous test, can select the matching rows:
const rows = raw_data.filter(r => r[0] >= 2007 && r[0] <= 2024 && r[2] > 0);
Live example (click to show)
function SheetJSAoAFiltered() { const [rows, setRows] = React.useState([]); React.useEffect(() => { (async() =>{ /* parse workbook */ const url = "https://docs.sheetjs.com/PortfolioSummary.xls"; const workbook = XLSX.read(await (await fetch(url)).arrayBuffer()); /* get first worksheet */ const worksheet = workbook.Sheets[workbook.SheetNames[0]]; const raw_data = XLSX.utils.sheet_to_json(worksheet, {header:1}); /* fill years */ var last_year = 0; raw_data.forEach(r => last_year = r[0] = (r[0] != null ? r[0] : last_year)); /* select data rows */ const rows = raw_data.filter(r => r[0] >= 2007 && r[0] <= 2024 && r[2] > 0); /* display data */ setRows(rows); })(); }, []); return ( <pre>{rows.map(r => JSON.stringify(r)+"\n")}</pre> ); }
Generate Row Objects
Looking at the headers:
The desired data is in column I
. The column index can be calculated using
XLSX.utils.decode_col
11.
Column Index calculation (click to show)
function SheetJSDecodeCol() { const cols = ["A", "B", "I"]; return ( <table><thead><tr><th>Label</th><th>Index</th></tr></thead> <tbody>{cols.map(col => ( <tr> <td>{col}</td> <td>{XLSX.utils.decode_col(col)}</td> </tr> ))}</tbody> </table> ); }
The desired columns are:
Column | Description | Property in Object |
---|---|---|
A / 0 | Fiscal Year | FY |
B / 1 | Fiscal Quarter (if applicable) | FQ |
I / 8 | Total Dollars Outstanding | total |
An Array#map
over the data can generate the desired row objects:
const objects = rows.map(r => ({FY: r[0], FQ: r[1], total: r[8]}));
This will generate an array of row objects. Each row object will look like the following row:
// 2016 Q1 - $1220.3 (billion)
{ "FY": 2016, "FQ": "Q1", "total": 1220.3 }
Live example (click to show)
function SheetJSObjects() { const [rows, setRows] = React.useState([]); React.useEffect(() => { (async() =>{ /* parse workbook */ const url = "https://docs.sheetjs.com/PortfolioSummary.xls"; const workbook = XLSX.read(await (await fetch(url)).arrayBuffer()); /* get first worksheet */ const worksheet = workbook.Sheets[workbook.SheetNames[0]]; const raw_data = XLSX.utils.sheet_to_json(worksheet, {header:1}); /* fill years */ var last_year = 0; raw_data.forEach(r => last_year = r[0] = (r[0] != null ? r[0] : last_year)); /* select data rows */ const rows = raw_data.filter(r => r[0] >= 2007 && r[0] <= 2024 && r[2] > 0); /* generate row objects */ const objects = rows.map(r => ({FY: r[0], FQ: r[1], total: r[8]})); /* display data */ setRows(objects); })(); }, []); return ( <pre>{rows.map(r => JSON.stringify(r)+"\n")}</pre> ); }
Present Data
At this point, objects
is an array of objects.
ReactJS
The live demos in this example use ReactJS. In ReactJS, arrays of objects are best presented in simple HTML tables12:
<table>
<thead><tr><th>Fiscal Year</th><th>Quarter</th><th>Total (in $B)</th></tr></thead>
<tbody>
{objects.map((o,R) => ( <tr key={R}>
<td>{o.FY}</td>
<td>{o.FQ}</td>
<td>{o.total}</td>
</tr>))}
</tbody>
</table>
Vanilla JS
https://sheetjs.com/sl.html is a hosted version of this demo.
Without a framework, HTML table row elements can be programmatically created
with document.createElement
and added to the table body element. For example,
if the page has a stub table:
<table>
<thead><tr><th>Fiscal Year</th><th>Quarter</th><th>Total (in $B)</th></tr></thead>
<tbody id="tbody"></tbody>
</table>
TR
elements can be added to the table body using appendChild
:
/* add rows to table body */
objects.forEach(o => {
const row = document.createElement("TR");
row.innerHTML = `<td>${o.FY}</td><td>${o.FQ||""}</td><td>${o.total}</td>`;
tbody.appendChild(row);
});
Command-Line Tools
In the command line, there are ways to display data in a table:
FY FQ Total
-- -- -----
2007 516
2013 Q1 961.9
For data pipelines, tab-separated rows are strongly recommended:
/* print header row*/
console.log(`FY\tFQ\tTotal`);
/* print tab-separated values */
objects.forEach(o => {
console.log(`${o.FY}\t${o.FQ||""}\t${o.total}`);
});
Live Demo
This demo runs in the web browser! It should automatically fetch the data file and display a table.
This example includes a row count that can be increased or decreased
function StudentAidTotal() { const [rows, setRows] = React.useState([]); const [num, setNum] = React.useState(5); React.useEffect(() => { (async() =>{ /* parse workbook */ const url = "https://docs.sheetjs.com/PortfolioSummary.xls"; const workbook = XLSX.read(await (await fetch(url)).arrayBuffer()); /* get first worksheet */ const worksheet = workbook.Sheets[workbook.SheetNames[0]]; const raw_data = XLSX.utils.sheet_to_json(worksheet, {header:1}); /* fill years */ var last_year = 0; raw_data.forEach(r => last_year = r[0] = (r[0] != null ? r[0] : last_year)); /* select data rows */ const rows = raw_data.filter(r => r[0] >= 2007 && r[0] <= 2024 && r[2] > 0); /* generate row objects */ const objects = rows.map(r => ({FY: r[0], FQ: r[1], total: r[8]})); /* display data */ setRows(objects); })(); }, []); return ( <> <a onClick={()=>{setNum(Math.max(num-5,0))}}>Show Less </a> <b>Showing {num} rows </b> <a onClick={()=>{setNum(num+5)}}>Show More</a> <table> <thead><tr><th>Fiscal Year</th><th>Quarter</th><th>Total (in $B)</th></tr></thead> <tbody> {rows.slice(0, num).map((o,R) => ( <tr key={R}> <td>{o.FY}</td> <td>{o.FQ}</td> <td>{o.total}</td> </tr>))} </tbody> </table> </> ); }
Run the Demo Locally
- Web Browser
- Command-Line (NodeJS)
- Desktop App
- Mobile App
Save the following script to SheetJSStandaloneDemo.html
:
<body>
<table>
<thead><tr><th>Fiscal Year</th><th>Quarter</th><th>Total (in $B)</th></tr></thead>
<tbody id="tbody"></tbody>
</table>
<script src="https://cdn.sheetjs.com/xlsx-0.20.3/package/dist/xlsx.full.min.js"></script>
<script>
(async() => {
/* parse workbook */
const url = "https://docs.sheetjs.com/PortfolioSummary.xls";
const workbook = XLSX.read(await (await fetch(url)).arrayBuffer());
/* get first worksheet */
const worksheet = workbook.Sheets[workbook.SheetNames[0]];
const raw_data = XLSX.utils.sheet_to_json(worksheet, {header:1});
/* fill years */
var last_year = 0;
raw_data.forEach(r => last_year = r[0] = (r[0] != null ? r[0] : last_year));
/* select data rows */
const rows = raw_data.filter(r => r[0] >= 2007 && r[0] <= 2024 && r[2] > 0);
/* generate row objects */
const objects = rows.map(r => ({FY: r[0], FQ: r[1], total: r[8]}));
/* add rows to table body */
objects.forEach(o => {
const row = document.createElement("TR");
row.innerHTML = ``;
tbody.appendChild(row);
});
})();
</script>
</body>
After saving the file, run a local web server in the folder with the HTML file. For example, if NodeJS is installed:
npx http-server .
The server process will display a URL (typically http://127.0.0.1:8080
). Open
http://127.0.0.1:8080/SheetJSStandaloneDemo.html
in your browser.
Install the dependencies:
- NodeJS
- Bun
npm i --save https://cdn.sheetjs.com/xlsx-0.20.3/xlsx-0.20.3.tgz
bun install https://cdn.sheetjs.com/xlsx-0.20.3/xlsx-0.20.3.tgz
Save the following script to SheetJSNodeJS.js
:
const XLSX = require("xlsx");
(async() => {
/* parse workbook */
const url = "https://docs.sheetjs.com/PortfolioSummary.xls";
const workbook = XLSX.read(await (await fetch(url)).arrayBuffer());
/* get first worksheet */
const worksheet = workbook.Sheets[workbook.SheetNames[0]];
const raw_data = XLSX.utils.sheet_to_json(worksheet, {header:1});
/* fill years */
var last_year = 0;
raw_data.forEach(r => last_year = r[0] = (r[0] != null ? r[0] : last_year));
/* select data rows */
const rows = raw_data.filter(r => r[0] >= 2007 && r[0] <= 2024 && r[2] > 0);
/* generate row objects */
const objects = rows.map(r => ({FY: r[0], FQ: r[1], total: r[8]}));
/* print header row*/
console.log(`FY\tQ\tTotal`);
/* print tab-separated values */
objects.forEach(o => {
console.log(`${o.FY}\t${o.FQ||""}\t${o.total}`);
});
})();
After saving the script, run the script:
- NodeJS
- Bun
node SheetJSNodeJS.js
bun run SheetJSNodeJS.js
This script will print the rows in tab-separated values (TSV) format:
FY Q Total
2007 516
2008 577
...
2013 Q1 961.9
2013 Q2 998.6
2013 Q3 1006.8
...
Save the following script to SheetJSNW.html
:
<body>
<table>
<thead><tr><th>Fiscal Year</th><th>Quarter</th><th>Total (in $B)</th></tr></thead>
<tbody id="tbody"></tbody>
</table>
<script src="https://cdn.sheetjs.com/xlsx-0.20.3/package/dist/xlsx.full.min.js"></script>
<script>
(async() => {
/* parse workbook */
const url = "https://docs.sheetjs.com/PortfolioSummary.xls";
const workbook = XLSX.read(await (await fetch(url)).arrayBuffer());
/* get first worksheet */
const worksheet = workbook.Sheets[workbook.SheetNames[0]];
const raw_data = XLSX.utils.sheet_to_json(worksheet, {header:1});
/* fill years */
var last_year = 0;
raw_data.forEach(r => last_year = r[0] = (r[0] != null ? r[0] : last_year));
/* select data rows */
const rows = raw_data.filter(r => r[0] >= 2007 && r[0] <= 2024 && r[2] > 0);
/* generate row objects */
const objects = rows.map(r => ({FY: r[0], FQ: r[1], total: r[8]}));
/* add rows to table body */
objects.forEach(o => {
const row = document.createElement("TR");
row.innerHTML = ``;
tbody.appendChild(row);
});
})();
</script>
</body>
Save the following to package.json
:
{
"name": "sheetjs-nwjs",
"author": "sheetjs",
"version": "0.0.0",
"main": "SheetJSNW.html",
"dependencies": {
"nw": "0.77.0",
"xlsx": "https://cdn.sheetjs.com/xlsx-0.20.3/xlsx-0.20.3.tgz"
}
}
Install dependencies and run:
npm i
npx nw .
The app will show the data in a table.
Follow the Environment Setup of the React Native documentation before testing the demo.
For Android testing, React Native requires Java 11. It will not work with current Java releases.
In React Native, there are a number of ways to display rows of data. This demo
uses the native FlatList
component.
Create a new project by running the following commands in the Terminal:
npx [email protected] init SheetJSSL --version="0.72.4"
cd SheetJSSL
npm i -S https://cdn.sheetjs.com/xlsx-0.20.3/xlsx-0.20.3.tgz
Save the following to App.tsx
in the project:
import React, { useState } from 'react';
import { Alert, Button, SafeAreaView, Text, View, FlatList } from 'react-native';
import { utils, version, read } from 'xlsx';
const Item = ({FY, FQ, total}) => (
<View style={{borderColor: "#000000", borderWidth: 1}}>
<Text style={{fontSize: 12}}>{String(FY)} {String(FQ||"")} : ${String(total)} B</Text>
</View>
);
const App = () => {
const [rows, setRows] = React.useState([]);
React.useEffect(() => { (async() =>{
/* parse workbook */
const url = "https://docs.sheetjs.com/PortfolioSummary.xls";
const workbook = read(await (await fetch(url)).arrayBuffer());
/* get first worksheet */
const worksheet = workbook.Sheets[workbook.SheetNames[0]];
const raw_data = utils.sheet_to_json(worksheet, {header:1});
/* fill years */
var last_year = 0;
raw_data.forEach(r => last_year = r[0] = (r[0] != null ? r[0] : last_year));
/* select data rows */
const rows = raw_data.filter(r => r[0] >= 2007 && r[0] <= 2024 && r[2] > 0);
/* generate row objects */
const objects = rows.map(r => ({FY: r[0], FQ: r[1], total: r[8]}));
/* display data */
setRows(objects);
})(); }, []);
return ( <SafeAreaView>
<View style={{ marginTop: 32, padding: 24 }}>
<Text style={{ fontSize: 24, fontWeight: 'bold' }}>SheetJS {version} Import Demo</Text>
<FlatList
data={rows}
renderItem={({item}) => <Item FQ={item.FQ} FY={item.FY} total={item.total} />}
keyExtractor={item => String(item.FY) + (item.FQ||"")}
/>
</View>
</SafeAreaView> );
}
export default App;
- Android
- iOS
The Android demo has been tested in Windows 10 and in macOS.
Test the app in the Android simulator:
npx react-native start
Once Metro is ready, it will display the commands:
r - reload the app
d - open developer menu
i - run on iOS
a - run on Android
Press a
to run on Android.
The demo also runs on real Android devices! After enabling USB debugging13, the Android device can be connected to the computer with a USB cable.
This demo runs in iOS and requires a Macintosh computer with Xcode installed.
Test the app in the iOS simulator:
npm run ios
When the app is loaded, the data will be displayed in rows.
Footnotes
-
The dataset URL has changed many times over the years. The current location for the CC0-licensed dataset can be found by searching for "National Student Loan Data System" on
data.gov
.PortfolioSummary.xls
is the file name within the dataset. ↩ -
See "Workbook Object" ↩
-
See "Workbook Object" ↩
-
See "Sheet Objects" ↩
-
See "Running on Device" in the React Native documentation for more details. ↩