The D3Blocks library also contains various helper functions to get the data in the right shape for the desired chart.

Export to HTML

Each block can be exported to HTML using the return_html parameter.

# load library
from d3blocks import D3Blocks

# Initialize
d3 = D3Blocks()

# Get data
df = d3.import_example(data='energy')

# Return HTML for Sankey
html = d3.sankey(df, return_html=True)

vec2adjmat

Convert source and target into adjacency matrix.

param source:

The source node.

type source:

list

param target:

The target node.

type target:

list

param weight:

The Weights between the source-target values

type weight:

list of int

param symmetric:

Make the adjacency matrix symmetric with the same number of rows as columns. The default is True.

type symmetric:

bool, optional

param aggfunc:
Aggregate function in case multiple values exists for the same relationship.
  • ‘sum’ (default)

type aggfunc:

str, optional

returns:

adjacency matrix.

rtype:

pd.DataFrame

Examples

>>> # Initialize
>>> d3 = D3Blocks()
>>> #
>>> # Load example
>>> df = d3.import_example('energy')
>>> #
>>> # Convert to adjmat
>>> adjmat = d3.vec2adjmat(df['source'], df['target'], df['weight'])

adjmat2vec

Convert adjacency matrix into vector with source and target.

param adjmat:

Adjacency matrix.

type adjmat:

pd.DataFrame()

param min_weight:

edges are returned with a minimum weight.

type min_weight:

float

returns:

nodes that are connected based on source and target

rtype:

pd.DataFrame()

Examples

>>> # Initialize
>>> d3 = D3Blocks()
>>> #
>>> # Load example
>>> df = d3.import_example('energy')
>>> Convert into adjmat
>>> adjmat = d3.vec2adjmat(df['source'], df['target'], df['weight'])
>>> #
>>> # Convert back to vector
>>> vector = d3.adjmat2vec(adjmat)

Examples

Import example dataset from github source.

Import one of the few datasets from github sourcek.

param data:
Example datasets:
  • “movingbubbles”

  • “random_time”

  • “timeseries”

  • “bigbang”

  • “southern_nebula_internet”

  • “climate”

  • “mnist”

  • “animals”

Datazets:
  • “energy”

  • “stormofswords”

  • “southern_nebula”

  • “cancer”

  • “breast_cancer”

  • “iris”

  • “occupancy”

type data:

str

param n:

Number of events (samples).

type n:

int, (default: 1000).

param c:

Number of classes.

type c:

int, (default: 100).

param date_start:
Start date.
  • “17-12-1903 00:00:00” : start date

type date_start:

str, (default: None)

param date_stop:
Stop date.
  • “17-12-1903 23:59:59” : Stop date

type date_stop:

str, (default: None)

returns:

Dataset containing mixed features.

rtype:

pd.DataFrame()

Saving Charts

Each d3block contains saving functionality to save your chart to a SVG image. The save functionality can be enabled by setting the ```