I would like to create a directed graph with use of the networkx library in python.

I have a pandas dataframe that looks like this:

                                 Head Mounted Display  Marker  Smartphone
    2D data extrusion                               3       0           1   
    AgiSoft PhotoScan 3D design                     1       2           2   
    AuGeo Esri AR template                          1       1           2   
    BIM                                             1       1           0   
    Blender 3D design                               0       2           4   
    Bluetooth localization                          1       1           0   
    CityEngine                                      3       1           2   
    GIS data processing                             3       1           2   
    GNSS localization                               1       2           4   
    Google ARCore                                   0       1           5   
    Google SketchUp 3D design                       1       2           0   
    Image Stitching                                 1       1           4   
    Java Development Kit                            0       1           0   
    SLAM                                            1       2           2   
    Unity 3D                                        8      12          10   
    Unreal Engine                                   1       1           0   
    Vuforia                                         2       7           3

As input for the "networkx.DiGraph.add_weighted_edges_from" function I need to format this in a list of 3-tuples like this:

('Head Mounted Display', '2D data extrusion', 3),
('Head Mounted Display', 'Agisoft PhotoScan 3D design', 1),
('Head Mounted Display','AuGeo Esri AR template', 1),
etc...

Furthermore, tuples that have a weight of 0 such as:

('Marker', '2D data extrusion', 0)

need to be removed from the list.

Anyone any idea how to do this?

Thanks in advance!

CodePudding user response：

Use df.columns[0] to get 'HeadMountedDisplay' and df.index[i] to get the row names. Note that df refers to your df name.

Then use tupling with a conditional:

tuple((df.columns[0], df.index[i], df[df.columns[0]][i]) for i in range(len(df)) if df[df.columns[0]][i] is not 0)

CodePudding user response：

You can follow the code below

lstOfTuples = []
for i in range(df.shape[0]):
    for j in range(df.shape[1]):
        index = df.index[i]
        col = df.columns[j]
        value = float(df.loc[index, col])
        if value > 0:
            lstOfTuples.append((col, index, value))
lstOfTuples

Create a directed graph like this

G = nx.Graph()
G.add_weighted_edges_from(ebunch_to_add=lstOfTuples)

CodePudding user response：

You can create the list of required tuples as follows:

def createTuples(df, onColumn=0):
    sze = df.shape[0]
    colName = list(df.columns)[onColumn]
    rslt = [] 
    for r in range(sze):
        if df.iloc[r][onColumn] > 0:
            rslt.append((colName, df.iloc[r].name, df.iloc[r][onColumn]))
    return rslt  

This approach allows you to designate the column heading you want to use in the first tuple position.

CodePudding user response：

Using .melt will help to get you the shape you are interested in. Here's a reproducible example:

import networkx as nx
import pandas as pd

# create a dummy dataframe with a similar structure
df = pd.DataFrame(zip(range(6), range(5, -1, -1)))
df.columns = list("ab")
df.index = list("qwerty")

# flatten the dataframe for easier processing
flat = df.melt(ignore_index=False).reset_index()

# ignore 0
mask = flat["value"] > 0
flat = flat.loc[mask]

# create a directed graphp
G = nx.DiGraph()

# fill-in with edges
for start, end, weight in flat.values:
    G.add_edge(start, end, weight=weight)

print(G.nodes())  # ['w', 'a', 'e', 'r', 't', 'y', 'q', 'b']
print(
    G.edges()
)  # [('w', 'a'), ('w', 'b'), ('e', 'a'), ('e', 'b'), ('r', 'a'), ('r', 'b'), ('t', 'a'), ('t', 'b'), ('y', 'a'), ('q', 'b')]