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https://github.com/opensource9ja/danfojs
Danfo.js is an open source, JavaScript library providing high performance, intuitive, and easy to use data structures for manipulating and processing structured data.
https://github.com/opensource9ja/danfojs
danfojs data-analysis data-analytics data-manipulation data-science dataframe javascript pandas plotting-charts stream-data stream-processing table tensorflow tensors
Last synced: about 2 months ago
JSON representation
Danfo.js is an open source, JavaScript library providing high performance, intuitive, and easy to use data structures for manipulating and processing structured data.
- Host: GitHub
- URL: https://github.com/opensource9ja/danfojs
- Owner: javascriptdata
- License: mit
- Created: 2020-05-13T21:53:26.000Z (over 4 years ago)
- Default Branch: dev
- Last Pushed: 2024-07-08T17:05:40.000Z (2 months ago)
- Last Synced: 2024-08-01T17:37:01.457Z (about 2 months ago)
- Topics: danfojs, data-analysis, data-analytics, data-manipulation, data-science, dataframe, javascript, pandas, plotting-charts, stream-data, stream-processing, table, tensorflow, tensors
- Language: TypeScript
- Homepage: https://danfo.jsdata.org/
- Size: 80.1 MB
- Stars: 4,731
- Watchers: 31
- Forks: 208
- Open Issues: 118
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- Funding: .github/FUNDING.yml
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
- awesome-imgcook - opensource9ja/danfojs - danfo.js is an open source, JavaScript library providing high performance, intuitive, and easy to use data structures for manipulating and processing structured data. (JavaScript packages for machine learning / Feature engineering)
README
-----------------
## Danfojs: powerful javascript data analysis toolkit
[](https://www.jsdelivr.com/package/npm/danfojs)
[](https://coveralls.io/github/opensource9ja/danfojs)
## What is it?
**Danfo.js** is a javascript package that provides fast, flexible, and expressive data
structures designed to make working with "relational" or "labeled" data both
easy and intuitive. It is heavily inspired by [Pandas](https://pandas.pydata.org/pandas-docs/stable/) library, and provides a similar API. This means that users familiar with [Pandas](https://pandas.pydata.org/pandas-docs/stable/), can easily pick up danfo.js.
## Main Features
- Danfo.js is fast and supports Tensorflow.js tensors out of the box. This means you can [convert Danfo data structure](https://danfo.jsdata.org/api-reference/dataframe/dataframe.tensor) to Tensors.
- Easy handling of [missing-data](https://danfo.jsdata.org/getting-started#missing-data) (represented as
`NaN`) in floating point as well as non-floating point data
- Size mutability: columns can be [inserted/deleted](https://danfo.jsdata.org/api-reference/dataframe#combining-comparing-joining-merging) from DataFrame
- Automatic and explicit [alignment](https://danfo.jsdata.org/api-reference/dataframe#reindexing-selection-label-manipulation): objects can
be explicitly aligned to a set of labels, or the user can simply
ignore the labels and let `Series`, `DataFrame`, etc. automatically
align the data for you in computations
- Powerful, flexible [groupby](https://danfo.jsdata.org/api-reference/groupby) functionality to perform
split-apply-combine operations on data sets, for both aggregating
and transforming data
- Make it easy to convert Arrays, JSONs, List or Objects, Tensors and
differently-indexed data structures
into DataFrame objects
- Intelligent label-based [slicing](https://danfo.jsdata.org/api-reference/dataframe/danfo.dataframe.loc), [fancy indexing](https://danfo.jsdata.org/api-reference/dataframe/danfo.dataframe.iloc), and [querying](https://danfo.jsdata.org/api-reference/dataframe/danfo.dataframe.query) of
large data sets
- Intuitive [merging](https://danfo.jsdata.org/api-reference/general-functions/danfo.merge) and [joining](https://danfo.jsdata.org/api-reference/general-functions/danfo.concat) data
sets
- Robust IO tools for loading data from [flat-files](https://danfo.jsdata.org/api-reference/input-output)
(CSV, Json, Excel).
- Powerful, flexible and intutive API for [plotting](https://danfo.jsdata.org/api-reference/plotting) DataFrames and Series interactively.
- [Timeseries](https://danfo.jsdata.org/api-reference/series#accessors)-specific functionality: date range
generation and date and time properties.
- Robust data preprocessing functions like [OneHotEncoders](https://danfo.jsdata.org/api-reference/general-functions/danfo.onehotencoder), [LabelEncoders](https://danfo.jsdata.org/api-reference/general-functions/danfo.labelencoder), and scalers like [StandardScaler](https://danfo.jsdata.org/api-reference/general-functions/danfo.standardscaler) and [MinMaxScaler](https://danfo.jsdata.org/api-reference/general-functions/danfo.minmaxscaler) are supported on DataFrame and Series
## Installation
There are three ways to install and use Danfo.js in your application
* For Nodejs applications, you can install the [__danfojs-node__]() version via package managers like yarn and/or npm:
```bash
npm install danfojs-node
or
yarn add danfojs-node
```
For client-side applications built with frameworks like React, Vue, Next.js, etc, you can install the [__danfojs__]() version:
```bash
npm install danfojs
or
yarn add danfojs
```
For use directly in HTML files, you can add the latest script tag from [JsDelivr](https://www.jsdelivr.com/package/npm/danfojs) to your HTML file:
```html
```
See all available versions [here](https://www.jsdelivr.com/package/npm/danfojs)
### Quick Examples
* [Danfojs with HTML and vanilla JavaScript on CodePen](https://codepen.io/risingodegua/pen/bGpwyYW)
* [Danfojs with React on Code Sandbox](https://codesandbox.io/s/using-danfojs-in-react-dwpv54?file=/src/App.js)
* [Danfojs on ObservableHq](https://observablehq.com/@risingodegua/using-danfojs-on-observablehq)
* [Danfojs in Nodejs on Replit](https://replit.com/@RisingOdegua/Danfojs-in-Nodejs)
### Example Usage in the Browser
```html
Document
dfd.readCSV("https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv")
.then(df => {
df['AAPL.Open'].plot("div1").box() //makes a box plot
df.plot("div2").table() //display csv as table
new_df = df.setIndex({ column: "Date", drop: true }); //resets the index to Date column
new_df.head().print() //
new_df.plot("div3").line({
config: {
columns: ["AAPL.Open", "AAPL.High"]
}
}) //makes a timeseries plot
}).catch(err => {
console.log(err);
})
```
Output in Browser:
### Example usage in Nodejs
```javascript
const dfd = require("danfojs-node");
const file_url =
"https://web.stanford.edu/class/archive/cs/cs109/cs109.1166/stuff/titanic.csv";
dfd
.readCSV(file_url)
.then((df) => {
//prints the first five columns
df.head().print();
// Calculate descriptive statistics for all numerical columns
df.describe().print();
//prints the shape of the data
console.log(df.shape);
//prints all column names
console.log(df.columns);
// //prints the inferred dtypes of each column
df.ctypes.print();
//selecting a column by subsetting
df["Name"].print();
//drop columns by names
let cols_2_remove = ["Age", "Pclass"];
let df_drop = df.drop({ columns: cols_2_remove, axis: 1 });
df_drop.print();
//select columns by dtypes
let str_cols = df_drop.selectDtypes(["string"]);
let num_cols = df_drop.selectDtypes(["int32", "float32"]);
str_cols.print();
num_cols.print();
//add new column to Dataframe
let new_vals = df["Fare"].round(1);
df_drop.addColumn("fare_round", new_vals, { inplace: true });
df_drop.print();
df_drop["fare_round"].round(2).print(5);
//prints the number of occurence each value in the column
df_drop["Survived"].valueCounts().print();
//print the last ten elementa of a DataFrame
df_drop.tail(10).print();
//prints the number of missing values in a DataFrame
df_drop.isNa().sum().print();
})
.catch((err) => {
console.log(err);
});
```
Output in Node Console:
## Notebook support
* VsCode nodejs notebook extension now supports Danfo.js. See guide [here](https://marketplace.visualstudio.com/items?itemName=donjayamanne.typescript-notebook)
* ObservableHQ Notebooks. See example notebook [here](https://observablehq.com/@risingodegua/using-danfojs-on-observablehq)
#### [See the Official Getting Started Guide](https://danfo.jsdata.org/getting-started)
## Documentation
The official documentation can be found [here](https://danfo.jsdata.org)
## Danfo.js Official Book
We published a book titled "Building Data Driven Applications with Danfo.js". Read more about it [here](https://danfo.jsdata.org/building-data-driven-applications-with-danfo.js-book)
## Discussion and Development
Development discussions take place [here](https://github.com/opensource9ja/danfojs/discussions).
## Contributing to Danfo
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. A detailed overview on how to contribute can be found in the [contributing guide](https://danfo.jsdata.org/contributing-guide).
#### Licence [MIT](https://github.com/opensource9ja/danfojs/blob/master/LICENCE)
#### Created by [Rising Odegua](https://github.com/risenW) and [Stephen Oni](https://github.com/steveoni)
