Reputation: 21
I have the table below that I read into a dataFrame:
n,next_n
1,2
1,3
1,6
2,4
2,8
3,5
3,9
4,7
9,10
My recursive function should return multiple lists of numbers through the end.
For example if I select to see all the values associated with 9, I should get a list that reads [9,10].
Another example:
4 should yield [4,7]
3 yields two lists
[3,5]
[3,9,10]
def recursivenum(df,n): indices = list() indices.append(n) x = df[df['n'] == n].next_n if len(x) > 0: for p1 in df[df['n'] == n].next_n: indices = indices + recursivenum(df,p1) elif len(x) == 0: #Base case - There are no other values print(indices) return indices
When I run recursivenum(df,1)
I get
[7]
[8]
[5]
[10]
[6]
[1, 2, 4, 7, 8, 3, 5, 9, 10, 6]
Which is nothing compared to what I expect to see.
Upvotes: 2
Views: 341
Reputation: 323226
This is more like a network problem , you would like to create the directed graph , then from the root (1) to the leaf (any value with level 0)
import networkx as nx
G=nx.from_pandas_edgelist(df,source='n',target='next_n', edge_attr=None, create_using=nx.DiGraph())
paths=[]
for node in G:
if G.out_degree(node)==0: #it's a leaf
paths.append(nx.shortest_path(G, 1, node))
paths
Out[42]: [[1, 6], [1, 2, 8], [1, 3, 5], [1, 2, 4, 7], [1, 3, 9, 10]]
Upvotes: 1
Reputation: 105
If the array consists of tuples, try using a for loop.
def recursivenum(df,n):
indices = list()
for x,y in df:
if x == n:
indices.append([x,y])
return indices
Upvotes: 0