code: def connect_tri_edges_pd(trimesh):
      """
      Given a TriMesh element containing abstract edges compute edge
      segments directly connecting the source and target nodes. This
      operation depends on pandas and is a lot faster than the pure
      NumPy equivalent.
      """
      edges = trimesh.dframe().copy()
      edges.index.name = "trimesh_edge_index"
      edges = edges.drop("color", errors="ignore", axis=1).reset_index()
      nodes = trimesh.nodes.dframe().copy()
      nodes.index.name = "node_index"
      nodes = nodes.drop(["color", "z"], errors="ignore", axis=1)
      v1, v2, v3 = trimesh.kdims
      x, y, idx = trimesh.nodes.kdims[:3]
  
      df = pd.merge(
          edges, nodes, left_on=[v1.name], right_on=[idx.name]
      )
      df = df.rename(columns={x.name: "x0", y.name: "y0"})
      df = pd.merge(df, nodes, left_on=[v2.name], right_on=[idx.name])
      df = df.rename(columns={x.name: "x1", y.name: "y1"})
      df = pd.merge(df, nodes, left_on=[v3.name], right_on=[idx.name])
      df = df.rename(columns={x.name: "x2", y.name: "y2"})
      df = df.sort_values("trimesh_edge_index").drop(
          ["trimesh_edge_index"], axis=1
      )
      return df[["x0", "y0", "x1", "y1", "x2", "y2"]]
  
imports: import itertools
  import numpy
  import pandas
  import param
  from ..core import Dataset
  from ..core.boundingregion import BoundingBox
  from ..core.data import PandasInterface, default_datatype
  from ..core.operation import Operation
  from ..core.sheetcoords import Slice
  from ..core.util import cartesian_product, datetime_types, is_cyclic, is_nan, one_to_one, sort_topologically
label_desc: Use image node_id 7 for calling a global function with example usage: connect_tri_edges_pd(trimesh) and returns: df