Your interactive network visualizing dashboard
Documentation: Here
What is Jaal
Jaal is a python based interactive network visualizing tool built using Dash and Visdcc. Along with the basic features, Jaal also provides multiple option to play with the network data such as searching graph, filtering and even coloring nodes and edges in the graph. And all of this within 2 lines of codes :)
Requirements
Jaal requires following python packages,
- Dash
- dash_core_components
- dash_html_components
- dash_bootstrap_components
- visdcc
- pandas
Install
Installing Jaal is super easy, just do the following,
pip install jaal
And you are done :)
Note, it's recommended to create a virtual enivornment before installing. This can be easily done using python -m venv myenv
and then to activate the env we need,
- (Windows)
.\\myvenv\\Scripts\\activate.bat
- (Linux)
source myvenv/bin/activate
Getting started
After installing Jaal, we need to fetch the data and call plot
function in Jaal. This can be shown by playing with an included Game of Thrones dataset, as follows,
# import
from jaal import Jaal
from jaal.datasets import load_got
# load the data
edge_df, node_df = load_got()
# init Jaal and run server
Jaal(edge_df, node_df).plot()
Here first we import Jaal
main class and the dataset loading function load_got
. Later we load the GoT dataset from the datasets included in the package. This gives us two files,
- edge_df: its a pandas dataframe with atleast
from
andto
column, which represents the edge relationship between the entities - node_df: its an optional parameter, but should contains a
id
column with unique node names.
Note, edge_df is mandatory and node_df is optional. Also we can include additional columns in these files which are automatically conidered as edge or node features respectively.
After running the plot, the console will prompt the default localhost address (127.0.0.1:8050
) where Jaal is running. Access it to see the following dashboard,
Features
At present, the dashboard consist of following sections,
- Setting panel: here we can play with the graph data, i further contain following sections,
- Search: can be used to highlight a node in graph
- Filter: supports pandas query language and can be used to filter the graph data based on nodes or edge features.
- Color: can be used to color nodes or edges based on their categorical features. Note, currently only features with at max 20 cardinality are supported.
- Graph: the network graph in all its glory :)
Examples
1. Searching
2. Filtering
3. Coloring
Extra settings
Display edge label
To display labels over edges, we need to add a label
attribute (column) in the edge_df
. Also, it has to be in string
format. For example, using the GoT dataset, by adding the following line before the Jaal
call, we can display the edge labels.
# add edge labels
edge_df.loc[:, 'label'] = edge_df.loc[:, 'weight'].astype(str)
Directed edges
By default, Jaal
plot undirected edges. This setting can be changed by,
Jaal(edge_df, node_df).plot(directed=True)
Issue tracker
Please report any bug or feature idea using Jaal issue tracker: https://github.com/imohitmayank/jaal/issues
Collaboration
Any type of collaboration is appreciated. It could be testing, development, documentation and other tasks that is useful to the project. Feel free to connect with me regarding this.
Contact
You can connect with me on LinkedIn or mail me at [email protected].
License
Jaal is licensed under the terms of the MIT License (see the file LICENSE).