# graph_analyzer

The `graph_analyzer` provides a deep analytics of the current state of the
graph. Various different graph properties are extracted using NetworX.

The list of analytics that the module uses:

* **nodes**: Number of nodes.
* **edges**: Number of relationshps.
* **bridges**: Number of bridges.
* **articulation_points**: Number of articulation points.
* **avg_degree**: Average degree.
* **sorted_nodes_degree**: Sorted nodes degree.
* **self_loops**: Self loops.
* **is_bipartite**: Shows if the graph is bipartite.
* **is_plannar**: Shows if the graph is planar.
* **is_biconnected**: Shows if the graph is biconnected.
* **is_weakly_connected**: Shows if the graph is weakly connected.
* **number_of_weakly_components**: The number of weakly connected components.
* **is_strongly_connected**: Shows if the graph is strongly connected.
* **strongly_components**: The number of strongly connected components.
* **is_dag**: Shows if the graph is directed acyclic graph (DAG).
* **is_eulerian**: Shows if the graph is eulerian.
* **is_forest**: Shows if the graph is forest.
* **is_tree**: Shows if the graph is tree.

  
| Trait               | Value      |
| ------------------- | ---------- |
| **Module type**     | module     |
| **Implementation**  | Python     |
| **Graph direction** | undirected |
| **Edge weights**    | unweighted |
| **Parallelism**     | sequential |

## Procedures

> **Info**
>
> You can execute this algorithm on [graph projections, subgraphs or portions of the graph](https://memgraph.com/docs/advanced-algorithms/run-algorithms#run-procedures-on-subgraph).

### `analyze()`

The procedure analyzes the graph and returns information.

#### Input:

- `subgraph: Graph` (**OPTIONAL**) ➡ A specific subgraph, which is an [object of type Graph](https://memgraph.com/docs/advanced-algorithms/run-algorithms#run-procedures-on-subgraph) returned by the `project()` function, on which the algorithm is run. 
If subgraph is not specified, the algorithm is computed on the entire graph by default.

- `analyses: List[string] (default=NULL)` ➡ List of analytics names to be fetched. If provided with NULL, the whole set of analytics will be included.

#### Output:

- `name: string` ➡ The name of the analytics.
- `value: string` ➡ Analytics value, stored as a string.

#### Usage:

Use the following query to analyze the graph:

```cypher
CALL graph_analyzer.analyze() 
YIELD name, value
RETURN name, value;
```

### `analyze_subgraph()`

The procedure analyzes a subgraph and returns information.

#### Input:

- `subgraph: Graph` (**OPTIONAL**) ➡ A specific subgraph, which is an [object of type Graph](https://memgraph.com/docs/advanced-algorithms/run-algorithms#run-procedures-on-subgraph) returned by the `project()` function, on which the algorithm is run. 
If subgraph is not specified, the algorithm is computed on the entire graph by default.

- `vertices: List[Vertex]` ➡ Subset of vertices within a graph.
- `edges: List[Edge]` ➡ Subset of relationships in a graph for which analytics will take place.
- `analyses: List[string] (default=NULL)` ➡ List of analytics names to be fetched. If provided with NULL, the whole set of analytics will be included.

#### Output:

- `name: string` ➡ The name of the analytics.
- `value: string` ➡ Analytics value, stored as a string.

#### Usage:

Use the following query to analyze a subgraph:

```cypher
MATCH (n)-[e]-(m)
WITH COLLECT(n) AS nodes_subset, COLLECT(e) AS edges_subset
CALL graph_analyzer.analyze(nodes_subset, edges_subset) YIELD name, value
RETURN name, value;
```

### `help()`

Shows the manual page for `graph_analyzer`.

#### Input:

None.

#### Output:

- `name: string` ➡ The name of the procedure.
- `value: string` ➡ Explanation of the procedure.

#### Usage:

Use the following query to analyze the graph:

```cypher
CALL graph_analyzer.help()
YIELD name, value
RETURN name, value;
```

## Example

### Database state
 

The database contains the following data: 

![](https://memgraph.com/docs/pages/advanced-algorithms/available-algorithms/graph_analyzer/graph-analyzer-1.png)

Created with the following Cypher queries:

```cypher
MERGE (a:Node {id: 0}) MERGE (b:Node {id: 1}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 1}) MERGE (b:Node {id: 2}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 1}) MERGE (b:Node {id: 3}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 2}) MERGE (b:Node {id: 3}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 2}) MERGE (b:Node {id: 4}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 3}) MERGE (b:Node {id: 4}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 1}) MERGE (b:Node {id: 5}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 0}) MERGE (b:Node {id: 6}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 5}) MERGE (b:Node {id: 6}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 5}) MERGE (b:Node {id: 7}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 5}) MERGE (b:Node {id: 8}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 7}) MERGE (b:Node {id: 8}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 8}) MERGE (b:Node {id: 9}) CREATE (a)-[:RELATION]->(b);
MERGE (a:Node {id: 10}) MERGE (b:Node {id: 11}) CREATE (a)-[:RELATION]->(b);
```

### Analyze the graph
 

Get the values using the following query:

```cypher
CALL graph_analyzer.analyze([
    "nodes", "edges", "bridges", "articulation_points",
    "avg_degree", "is_dag", "is_tree", "strongly_components"
    ])
YIELD name, value
RETURN name, value;
```

Results:

```plaintext
+-------------------------------------------+-------------------------------------------+
| name                                      | value                                     |
+-------------------------------------------+-------------------------------------------+
| "Number of nodes"                         | "12"                                      |
| "Number of edges"                         | "14"                                      |
| "Number of bridges"                       | "2"                                       |
| "Number of articulation points"           | "3"                                       |
| "Average degree"                          | "1.1666666666666667"                      |
| "Is DAG"                                  | "True"                                    |
| "Is tree"                                 | "False"                                   |
| "Number of strongly connected components" | "12"                                      |
+-------------------------------------------+-------------------------------------------+
```