Venn diagrams

According to Wikipedia

a Venn diagram, also called a set diagram or logic diagram, shows all possible logical relations between a finite collection of different sets. These diagrams depict elements as points in the plane, and sets as regions inside closed curves. A Venn diagram consists of multiple overlapping closed curves, usually circles, each representing a set. The points inside a curve labelled S represent elements of the set S, while points outside the boundary represent elements not in the set S. This lends itself to intuitive visualizations; for example, the set of all elements that are members of both sets S and T, denoted S ∩ T and read "the intersection of S and T", is represented visually by the area of overlap of the regions S and T.

Venn diagrams take all of the standard parameters.

Data

The data format is unique to Venn diagrams, in provided as either a DataFrame, or a native (Python/JSON) list of dictionaries (maps in Python) with the following elements:

• Either sets or name to specify the sets
• size to specify the size of the set or intersection of sets

In more detail:

setsList[string]

The sets element lists the sets whose intersection is represented by a particular area in the grep, for example sets: ['A'] represents the size of set "A" and sets: ['A', 'B'] the size of the intersection between sets "A" and "B".

namestring

Alternatively, the sets may be provided as an ampersand-separated string, like this: name: 'A&B', which is in all ways equivalent to sets: ['A', 'B']. Pandas or other data frames can be used with this parameter like this:

import doodl
import pandas as pd

df = pd.DataFrame([
    { "name": "A",     "size": 12 }, 
    { "name": "B",     "size": 12 },
    { "name": "C",     "size": 12 },
    { "name": "A&B",   "size":  2 },
    { "name": "A&C",   "size":  3 },
    { "name": "B&C",   "size":  4 },
    { "name": "A&B&C", "size":  1 }
])

doodl.vennchart(data=df)

or, if you want to use another column than the standard ones:

import doodl
import pandas as pd

df = pd.DataFrame([
    { 'company': 'A',     'sales':   450_000, 'clients': 163 },
    { 'company': 'B',     'sales': 1_520_000, 'clients': 564 },
    { 'company': 'C',     'sales':   994_000, 'clients': 762 },
    { 'company': 'A&B',   'sales':   226_000, 'clients':  46 },
    { 'company': 'A&C',   'sales':    51_000, 'clients':  12 },
    { 'company': 'B&C',   'sales':    67_000, 'clients':   9 },
    { 'company': 'A&B&C', 'sales':     4_000, 'clients':   4 },
])

doodl.vennchart(
    data=df,
    name='company',
    size='clients'
)

sizepositive number

The size parameter determines the area of the set or intersection to which it refers. The numbers will be scaled appropriately and automatically to be visually reasonable. The size much be greater than zero.

Here's an example of valid data (in Python):

[
    { 'sets': ['A'], 'size': 12 }, 
    { 'sets': ['B'], 'size': 12 },
    { 'sets': ['C'], 'size': 12 },
    { 'sets': ['A','B'], 'size': 2 },    # Intersection of sets A and B
    { 'sets': ['A','C'], 'size': 3 },    # Intersection of sets A and C
    { 'sets': ['B','C'], 'size': 4 },    # Intersection of sets B and C
    { 'sets': ['A','B','C'], 'size': 1 } # Intersection of sets A, B and C
]

Examples

The following:

<vennchart
    data="[
        { 'sets': ['A'], 'size': 12 }, 
        { 'sets': ['B'], 'size': 12 },
        { 'sets': ['C'], 'size': 12 },
        { 'sets': ['A','B'], 'size': 2 },
        { 'sets': ['A','C'], 'size': 3 },
        { 'sets': ['B','C'], 'size': 4 },
        { 'sets': ['A','B','C'], 'size': 1 }
    ]"
    width=500
    height=500
>
</vennchart>

all produce the following diagram: