<｜begin▁of▁sentence｜>### Instruction:
Assume you're working at a bustling restaurant, metaphorically envisioned as a network of tables(nodes) with paths between them(edges), represented as the dining establishment's blueprint: the tables are [1, 2, 3, 4] and the accessible walking paths are [(1, 2), (1, 3), (1, 4), (2, 3), (3, 4)]. There's a regular customer who's rather peculiar and insists on avoiding a certain table, for instance, Table 2. How could we use NetworkX's FilterAtlas to adjust our serving routine by filtering out this specific table along with its paths? Remember, don't just explain it theoretically. Let's put it into practice in our day-to-day service to ensure a seamless dining experience for our customers.
### Response:
import networkx as nx

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

# Define a filter function
filter_func = lambda node: node != 2

# Create a FilterAtlas view of the graph's node data
filtered_nodes = nx.classes.coreviews.FilterAtlas(G._node, filter_func)

# Print the nodes in the FilterAtlas
for node in filtered_nodes:
    print(node, filtered_nodes[node])
<|EOT|>
