JsPandas is a lightweight JavaScript library for data manipulation and analysis, inspired by the popular pandas library in Python. It provides flexible data structures and data analysis tools similar to pandas, enabling efficient data handling and manipulation in JavaScript.
- Read and write data from/to CSV, Excel, TSV, and JSON files
- Data manipulation functions such as filtering, sorting, grouping, and aggregating
- Apply functions to columns or rows
- Iterate over rows with
iterrows
method - Descriptive statistics
You can install JsPandas using npm:
npm install jspandas
const { Pandas } = require('jspandas');
// Create some sample data
const data = [
{ col1: 1, col2: 2, col3: 3 },
{ col1: 4, col2: 5, col3: 6 },
{ col1: 7, col2: 8, col3: 9 }
];
// Create a DataFrame using the Pandas class
const df = Pandas.DataFrame(data);
console.log(df);
const { Pandas } = require('jspandas');
// Read data from CSV file
const df = await Pandas.readCSV('data.csv');
console.log(df);
// Read data from Excel file
const df = await Pandas.readExcel('data.xlsx', 'Sheet1');
console.log(df);
// Read data from TSV file
const df = await Pandas.readTSV('data.tsv');
console.log(df);
// Read data from JSON file
const df = await Pandas.readJSON('data.json');
console.log(df);
await df.toCSV('output.csv');
// Write data to Excel file
await df.toEXCEL('output.xlsx');
// Write data to JSON file
await df.toJSON('output.json');
const { Pandas } = require('jspandas');
// Create some sample data
const data = [
{ col1: 1, col2: 2, col3: 3 },
{ col1: 4, col2: 5, col3: 6 },
{ col1: 7, col2: 8, col3: 9 }
];
const df = Pandas.DataFrame(data);
// Filter rows
const filteredDf = df.filter(row => row.col1 > 3);
console.log(filteredDf);
// Sort by column
const sortedDf = df.sortBy('col1', 'desc');
console.log(sortedDf);
// Group by column and aggregate
const groupedDf = df.groupBy('col1');
console.log(groupedDf);
const { Pandas } = require('jspandas');
// Create some sample data
const data = [
{ col1: 1, col2: 2, col3: 3 },
{ col1: 4, col2: 5, col3: 6 },
{ col1: 7, col2: 8, col3: 9 }
];
const df = Pandas.DataFrame(data);
// Apply function to columns
const dfColumnsApplied = df.apply(value => value * 2, 0);
console.log(dfColumnsApplied);
// Apply function to rows
const dfRowsApplied = df.apply(row => {
row['colSum'] = row['col1'] + row['col2'];
return row;
}, 1);
console.log(dfRowsApplied);