Matplotlib-venn and keeping lists of the entries Having come upon the wonderful little module of matplotlib-venn I've used it for a bit, I'm wondering if there's a nicer way of doing things than what I have done so far. I know that you can use the following lines for a very simple Venn diagram:

union = set1.union(set2).union(set3)
indicators = ['%d%d%d' % (a in set1, a in set2, a in set3) for a in union]
subsets = Counter(indicators)


... but also want to have lists of entries in the various combinations of the three sets.

import numpy as np
from matplotlib_venn import venn3, venn3_circles
from matplotlib import pyplot as plt
import pandas as pd

# Read data
data = pd.read_excel(input_file, sheetname=sheet)

# Create three sets of the lists to be compared
set_1 = set(data[compare[0]].dropna())
set_2 = set(data[compare[1]].dropna())
set_3 = set(data[compare[2]].dropna())

# Create a third set with all elements of the two lists
union = set_1.union(set_2).union(set_3)

# Gather names of all elements and list them in groups
lists = [[], [], [], [], [], [], []]
for gene in union:
    if (gene in set_1) and (gene not in set_2) and (gene not in set_3):
        lists[0].append(gene)
    elif (gene in set_1) and (gene in set_2) and (gene not in set_3):
        lists[1].append(gene)
    elif (gene in set_1) and (gene not in set_2) and (gene in set_3):
        lists[2].append(gene)
    elif (gene in set_1) and (gene in set_2) and (gene in set_3):
        lists[3].append(gene)
    elif (gene not in set_1) and (gene in set_2) and (gene not in set_3):
        lists[4].append(gene)
    elif (gene not in set_1) and (gene in set_2) and (gene in set_3):
        lists[5].append(gene)
    elif (gene not in set_1) and (gene not in set_2) and (gene in set_3):
        lists[6].append(gene)

# Write gene lists to file
ew = pd.ExcelWriter('../Gene lists/Venn lists/' + compare[0] + ' &amp; '
                    + compare[1] + ' &amp; ' + compare[2] + ' gene lists.xlsx')

pd.DataFrame(lists[0], columns=[compare[0]]) \
    .to_excel(ew, sheet_name=compare[0], index=False)

pd.DataFrame(lists[1], columns=[compare[0] + ' &amp; ' + compare[1]]) \
    .to_excel(ew, sheet_name=compare[0] + ' &amp; ' + compare[1], index=False)

pd.DataFrame(lists[2], columns=[compare[0] + ' &amp; ' + compare[2]]) \
    .to_excel(ew, sheet_name=compare[0] + ' &amp; ' + compare[2], index=False)

pd.DataFrame(lists[3], columns=['All']) \
    .to_excel(ew, sheet_name='All', index=False)

pd.DataFrame(lists[4], columns=[compare[1]]) \
    .to_excel(ew, sheet_name=compare[1], index=False)

pd.DataFrame(lists[5], columns=[compare[1] + ' &amp; ' + compare[2]]) \
    .to_excel(ew, sheet_name=compare[1] + ' &amp; ' + compare[2], index=False)

pd.DataFrame(lists[6], columns=[compare[2]]) \
    .to_excel(ew, sheet_name=compare[2], index=False)

ew.save()

# Count the elements in each group
subsets = [len(lists[0]), len(lists[4]), len(lists[1]), len(lists[6]),
           len(lists[2]), len(lists[5]), len(lists[3])]

# Basic venn diagram
fig = plt.figure(1)
ax = fig.add_subplot(1, 1, 1)
v = venn3(subsets, (compare[0], compare[1], compare[2]), ax=ax)
c = venn3_circles(subsets)

# Annotation
ax.annotate('Total genes:\n' + str(len(union)),
            xy=v.get_label_by_id('111').get_position() - np.array([-0.5,
                                                                   0.05]),
            xytext=(0,-70), ha='center', textcoords='offset points',
            bbox=dict(boxstyle='round,pad=0.5', fc='gray', alpha=0.3))

# Title
plt.title(compare[0] + ' &amp; ' + compare[1] + ' &amp; ' + compare[2] +
          ' gene expression overlap')

plt.show()


So, there's basically a lot of different cases, each handled manually, and I'm wondering if there's a more "automated" / less verbose / better way of doing this. For example, can I get out the entries from the three line code snippet in the beginning somehow?
Perhaps something like the following?

values_to_sets = {a : (a in set1, a in set2, a in set3) for a in union}
sets_to_values = {}
for a, s in values_to_sets.items():
    if s not in sets_to_values:
        sets_to_values[s] = []
    sets_to_values[s].append(a)
print(sets_to_values)


This first identifies each item with a tuple indicating which sets that item belongs to. Then you flip the dictionary mapping, where each tuple maps to a list of items belonging to the combination of sets indicated in the tuple.

You could even expand this to an arbitrary number of sets:

sets = [set1, set2, set3, set4]
values_to_sets = {a : (a in s for s in sets) for a in union}