Create edgelist from dataframe with groups in Python
I have the following data:
import pandas as pd
employee=["a","b","a","c","d","e","c","d","f"]
project=[1,1,2,2,2,3,3,4,4]
df=pd.DataFrame("employee":employee,
"project":project)
I want to make an edgelist from this dataframe. In the past when I was using R I used the following code:
edges<-unique(df %>% group_by(project) %>%
filter(n()>=2) %>% group_by(project) %>%
do(data.frame(t(combn(.$employee, 2)), stringsAsFactors=FALSE)))
edges<-subset(edges,as.numeric(edges$X1)-as.numeric(edges$X2)!=0)
However, I don't succeed when I want to do the same thing in Python. Can anybody help with some tips on how to transform this (probably via an adjacency matrix) into an edge-list.
The desired result should look something like this
employee1 employee2
A B
A C
C D
E C
D F
EDIT: I finally found my answer: pandas - reshape dataframe to edge list according to column values
python nodes networkx adjacency-matrix edges
asked Nov 14 '18 at 16:51
GerGer
2515
add a comment |
I have the following data:
import pandas as pd
employee=["a","b","a","c","d","e","c","d","f"]
project=[1,1,2,2,2,3,3,4,4]
df=pd.DataFrame("employee":employee,
"project":project)
I want to make an edgelist from this dataframe. In the past when I was using R I used the following code:
edges<-unique(df %>% group_by(project) %>%
filter(n()>=2) %>% group_by(project) %>%
do(data.frame(t(combn(.$employee, 2)), stringsAsFactors=FALSE)))
edges<-subset(edges,as.numeric(edges$X1)-as.numeric(edges$X2)!=0)
However, I don't succeed when I want to do the same thing in Python. Can anybody help with some tips on how to transform this (probably via an adjacency matrix) into an edge-list.
The desired result should look something like this
employee1 employee2
A B
A C
C D
E C
D F
EDIT: I finally found my answer: pandas - reshape dataframe to edge list according to column values
python nodes networkx adjacency-matrix edges
asked Nov 14 '18 at 16:51
GerGer
2515
add a comment |
I have the following data:
import pandas as pd
employee=["a","b","a","c","d","e","c","d","f"]
project=[1,1,2,2,2,3,3,4,4]
df=pd.DataFrame("employee":employee,
"project":project)
I want to make an edgelist from this dataframe. In the past when I was using R I used the following code:
edges<-unique(df %>% group_by(project) %>%
filter(n()>=2) %>% group_by(project) %>%
do(data.frame(t(combn(.$employee, 2)), stringsAsFactors=FALSE)))
edges<-subset(edges,as.numeric(edges$X1)-as.numeric(edges$X2)!=0)
However, I don't succeed when I want to do the same thing in Python. Can anybody help with some tips on how to transform this (probably via an adjacency matrix) into an edge-list.
The desired result should look something like this
employee1 employee2
A B
A C
C D
E C
D F
EDIT: I finally found my answer: pandas - reshape dataframe to edge list according to column values
python nodes networkx adjacency-matrix edges
asked Nov 14 '18 at 16:51
GerGer
2515
I have the following data:
import pandas as pd
employee=["a","b","a","c","d","e","c","d","f"]
project=[1,1,2,2,2,3,3,4,4]
df=pd.DataFrame("employee":employee,
"project":project)
I want to make an edgelist from this dataframe. In the past when I was using R I used the following code:
edges<-unique(df %>% group_by(project) %>%
filter(n()>=2) %>% group_by(project) %>%
do(data.frame(t(combn(.$employee, 2)), stringsAsFactors=FALSE)))
edges<-subset(edges,as.numeric(edges$X1)-as.numeric(edges$X2)!=0)
However, I don't succeed when I want to do the same thing in Python. Can anybody help with some tips on how to transform this (probably via an adjacency matrix) into an edge-list.
The desired result should look something like this
employee1 employee2
A B
A C
C D
E C
D F
EDIT: I finally found my answer: pandas - reshape dataframe to edge list according to column values
python nodes networkx adjacency-matrix edges
python nodes networkx adjacency-matrix edges
asked Nov 14 '18 at 16:51
GerGer
2515
asked Nov 14 '18 at 16:51
GerGer
2515
edited Nov 14 '18 at 17:02
Ger
asked Nov 14 '18 at 16:51
GerGer
2515
asked Nov 14 '18 at 16:51
GerGer
2515
asked Nov 14 '18 at 16:51
GerGer
2515
2515
add a comment |
add a comment |
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