<｜begin▁of▁sentence｜>### Instruction:
Imagine you are evaluating the potential value and connectivity of several properties within a bustling real estate market. In this scenario, we have four properties in consideration: Property 1, Property 2, Property 3, and Property 4. These properties are connected in a manner akin to a community network: Property 1 has connections to Properties 2 and 3, Property 2 extends a bridge to Property 4, and likewise, Property 3 connects with Property 4, forming a loop of associations between these estates.

Our appraisal involves analyzing the influence of these properties on the network, based on a concept similar to water flow where each property has a percolation state representing its likelihood of "transmitting" buying interest. The percolation state values for these properties are as follows: Property 1 has a percolation likelihood of 50%, Property 2 and Property 3 are both fully permissive with a percolation likelihood of 100%, and Property 4, which is currently undergoing issues that bar it from influencing the market, holds a percolation likelihood of 0%.

Your task, as an esteemed Real Estate Appraiser with a penchant for network analysis, is to appraise the percolation centrality for each of these properties. This measure will reveal which properties wield the greatest influence within this interconnected market network when considering their individual percolation states. The centrality figure will be a deciding factor for potential spot investment decisions. Employ the analytical tool, NetworkX, for this assessment, and ensure to draw conclusions that are tightly aligned with the percolation states and structure of the property network previously outlined.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(1, 2), (1, 3), (2, 4), (3, 4)])

# Define percolation states
states = {1: 0.5, 2: 1.0, 3: 1.0, 4: 0.0}

# Compute the percolation centrality
centrality = nx.percolation_centrality(G, states=states)

print('Percolation centrality:', centrality)
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