In this tutorial, you will learn how to merge nodes and attributes from different datasets in Pandas.
Suppose you have the first dataset as below:
Node Edge A B A D B N B A B X S C
And the second dataset has unique nodes and their properties as shown below:
Node Attribute A -1 B 0 C -1.5 D 1 ... N 1 ... X 0 Y -1.5 W -1.5 Z 1
Now in the below example, we will see how we can merge the second dataset nodes and attributes to the first dataset.
Example: Merge Nodes and Attributes from Second Dataset in Pandas
The following Python code will create a mapping from Node to color by set_index to Node, and map the current attribute numerical value into a color:
import networkx as nx
import pandas as pd
edges_df = pd.DataFrame({
'Node': ['A', 'A', 'B', 'B', 'B', 'S'],
'Edge': ['B', 'D', 'N', 'A', 'X', 'C']
})
# Abridged but contains values for all nodes in `edges_df`
attributes_df = pd.DataFrame({
'Node': ['A', 'B', 'C', 'D', 'N', 'S', 'X'],
'Attribute': [-1, 0, -1.5, 1, 1, 1.5, 0]
})
mapper = {-1.5: 'grey', -1: 'red', 0: 'orange', 1: 'yellow', 1.5: 'green'}
colour_map = attributes_df.set_index('Node')['Attribute'].map(mapper)
Color Map
Node A red B orange C grey D yellow N yellow S green X orange Name: Attribute, dtype: object
