Identifying ultimate parents in pandas dataframe
I have the following dataframe with a column of Child and a column of Parents:
import pandas as pd
df = pd.DataFrame({'Child': ['A1', 'A2', 'A3', 'A1', 'A1', 'A4', 'A2', 'A3'],
'Parent': ['B1', 'B2', 'A2', 'B3', 'A4', 'B4', 'B5', 'B6']})
df
Child Parent
0 A1 B1
1 A2 B2
2 A3 A2
3 A1 B3
4 A1 A4
5 A4 B4
6 A2 B5
7 A3 B6
There are duplicate children and some of them appear in the parent column. I would like to know the ultimate parents. This is a similar question to this one but with duplicates in the Child column. The output I would like is something like the following:
Child Links Ult_Parents
0 A1 (A1 - B1, A1 - B3, A1 - A4 - B4) (B1, B3, B4)
1 A2 (A2 - B2, A2 - B5) (B2, B5)
2 A3 (A3 - A2 - B2, A3 - A2 - B5, A3 - B6) (B2, B5, B6)
3 A4 (A4 - B4) (B4)
A1 has clear parents B1 and B3, but also B4 because it is linked to A4. A2 has simply B2 and B5. I am interested in the links between them but mainly on the ultimate parent.
python pandas loops dataframe for-loop
edited Nov 22 at 16:35
Ali AzG
585515
asked Nov 22 at 16:31
prmlmu
816
add a comment |
I have the following dataframe with a column of Child and a column of Parents:
import pandas as pd
df = pd.DataFrame({'Child': ['A1', 'A2', 'A3', 'A1', 'A1', 'A4', 'A2', 'A3'],
'Parent': ['B1', 'B2', 'A2', 'B3', 'A4', 'B4', 'B5', 'B6']})
df
Child Parent
0 A1 B1
1 A2 B2
2 A3 A2
3 A1 B3
4 A1 A4
5 A4 B4
6 A2 B5
7 A3 B6
There are duplicate children and some of them appear in the parent column. I would like to know the ultimate parents. This is a similar question to this one but with duplicates in the Child column. The output I would like is something like the following:
Child Links Ult_Parents
0 A1 (A1 - B1, A1 - B3, A1 - A4 - B4) (B1, B3, B4)
1 A2 (A2 - B2, A2 - B5) (B2, B5)
2 A3 (A3 - A2 - B2, A3 - A2 - B5, A3 - B6) (B2, B5, B6)
3 A4 (A4 - B4) (B4)
A1 has clear parents B1 and B3, but also B4 because it is linked to A4. A2 has simply B2 and B5. I am interested in the links between them but mainly on the ultimate parent.
python pandas loops dataframe for-loop
edited Nov 22 at 16:35
Ali AzG
585515
asked Nov 22 at 16:31
prmlmu
816
add a comment |
I have the following dataframe with a column of Child and a column of Parents:
import pandas as pd
df = pd.DataFrame({'Child': ['A1', 'A2', 'A3', 'A1', 'A1', 'A4', 'A2', 'A3'],
'Parent': ['B1', 'B2', 'A2', 'B3', 'A4', 'B4', 'B5', 'B6']})
df
Child Parent
0 A1 B1
1 A2 B2
2 A3 A2
3 A1 B3
4 A1 A4
5 A4 B4
6 A2 B5
7 A3 B6
There are duplicate children and some of them appear in the parent column. I would like to know the ultimate parents. This is a similar question to this one but with duplicates in the Child column. The output I would like is something like the following:
Child Links Ult_Parents
0 A1 (A1 - B1, A1 - B3, A1 - A4 - B4) (B1, B3, B4)
1 A2 (A2 - B2, A2 - B5) (B2, B5)
2 A3 (A3 - A2 - B2, A3 - A2 - B5, A3 - B6) (B2, B5, B6)
3 A4 (A4 - B4) (B4)
A1 has clear parents B1 and B3, but also B4 because it is linked to A4. A2 has simply B2 and B5. I am interested in the links between them but mainly on the ultimate parent.
python pandas loops dataframe for-loop
edited Nov 22 at 16:35
Ali AzG
585515
asked Nov 22 at 16:31
prmlmu
816
I have the following dataframe with a column of Child and a column of Parents:
import pandas as pd
df = pd.DataFrame({'Child': ['A1', 'A2', 'A3', 'A1', 'A1', 'A4', 'A2', 'A3'],
'Parent': ['B1', 'B2', 'A2', 'B3', 'A4', 'B4', 'B5', 'B6']})
df
Child Parent
0 A1 B1
1 A2 B2
2 A3 A2
3 A1 B3
4 A1 A4
5 A4 B4
6 A2 B5
7 A3 B6
There are duplicate children and some of them appear in the parent column. I would like to know the ultimate parents. This is a similar question to this one but with duplicates in the Child column. The output I would like is something like the following:
Child Links Ult_Parents
0 A1 (A1 - B1, A1 - B3, A1 - A4 - B4) (B1, B3, B4)
1 A2 (A2 - B2, A2 - B5) (B2, B5)
2 A3 (A3 - A2 - B2, A3 - A2 - B5, A3 - B6) (B2, B5, B6)
3 A4 (A4 - B4) (B4)
A1 has clear parents B1 and B3, but also B4 because it is linked to A4. A2 has simply B2 and B5. I am interested in the links between them but mainly on the ultimate parent.
python pandas loops dataframe for-loop
python pandas loops dataframe for-loop
edited Nov 22 at 16:35
Ali AzG
585515
asked Nov 22 at 16:31
prmlmu
816
edited Nov 22 at 16:35
Ali AzG
585515
asked Nov 22 at 16:31
prmlmu
816
edited Nov 22 at 16:35
Ali AzG
585515
edited Nov 22 at 16:35
Ali AzG
585515
edited Nov 22 at 16:35
Ali AzG
585515
585515
asked Nov 22 at 16:31
prmlmu
816
asked Nov 22 at 16:31
prmlmu
816
asked Nov 22 at 16:31
prmlmu
816
816
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
import networkx as nx
def all_descendants_nx():
DiG = nx.from_pandas_edgelist(df,'Parent','Child',create_using=nx.DiGraph())
return pd.DataFrame.from_records([(n1,n2) for n1 in DiG.nodes() for n2 in nx.ancestors(DiG, n1)], columns=['Child','Ult_Parents'])
df = all_descendants_nx()
df = df.loc[df.Ult_Parents.str.startswith("B")]
print(df)
df['Links'] = df.Child.astype('str') + ' - ' + df.Ult_Parents.astype('str')
df = df.groupby('Child').agg(lambda x: sorted(x.tolist())).reset_index()
print(df)
answered Nov 22 at 16:59
Charles R
825213
Thanks. How do I then plot the resulting DiGraph?
– prmlmu
Nov 23 at 17:20
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
import networkx as nx
def all_descendants_nx():
DiG = nx.from_pandas_edgelist(df,'Parent','Child',create_using=nx.DiGraph())
return pd.DataFrame.from_records([(n1,n2) for n1 in DiG.nodes() for n2 in nx.ancestors(DiG, n1)], columns=['Child','Ult_Parents'])
df = all_descendants_nx()
df = df.loc[df.Ult_Parents.str.startswith("B")]
print(df)
df['Links'] = df.Child.astype('str') + ' - ' + df.Ult_Parents.astype('str')
df = df.groupby('Child').agg(lambda x: sorted(x.tolist())).reset_index()
print(df)
answered Nov 22 at 16:59
Charles R
825213
Thanks. How do I then plot the resulting DiGraph?
– prmlmu
Nov 23 at 17:20
add a comment |
import networkx as nx
def all_descendants_nx():
DiG = nx.from_pandas_edgelist(df,'Parent','Child',create_using=nx.DiGraph())
return pd.DataFrame.from_records([(n1,n2) for n1 in DiG.nodes() for n2 in nx.ancestors(DiG, n1)], columns=['Child','Ult_Parents'])
df = all_descendants_nx()
df = df.loc[df.Ult_Parents.str.startswith("B")]
print(df)
df['Links'] = df.Child.astype('str') + ' - ' + df.Ult_Parents.astype('str')
df = df.groupby('Child').agg(lambda x: sorted(x.tolist())).reset_index()
print(df)
answered Nov 22 at 16:59
Charles R
825213
Thanks. How do I then plot the resulting DiGraph?
– prmlmu
Nov 23 at 17:20
add a comment |
import networkx as nx
def all_descendants_nx():
DiG = nx.from_pandas_edgelist(df,'Parent','Child',create_using=nx.DiGraph())
return pd.DataFrame.from_records([(n1,n2) for n1 in DiG.nodes() for n2 in nx.ancestors(DiG, n1)], columns=['Child','Ult_Parents'])
df = all_descendants_nx()
df = df.loc[df.Ult_Parents.str.startswith("B")]
print(df)
df['Links'] = df.Child.astype('str') + ' - ' + df.Ult_Parents.astype('str')
df = df.groupby('Child').agg(lambda x: sorted(x.tolist())).reset_index()
print(df)
answered Nov 22 at 16:59
Charles R
825213
import networkx as nx
def all_descendants_nx():
DiG = nx.from_pandas_edgelist(df,'Parent','Child',create_using=nx.DiGraph())
return pd.DataFrame.from_records([(n1,n2) for n1 in DiG.nodes() for n2 in nx.ancestors(DiG, n1)], columns=['Child','Ult_Parents'])
df = all_descendants_nx()
df = df.loc[df.Ult_Parents.str.startswith("B")]
print(df)
df['Links'] = df.Child.astype('str') + ' - ' + df.Ult_Parents.astype('str')
df = df.groupby('Child').agg(lambda x: sorted(x.tolist())).reset_index()
print(df)
answered Nov 22 at 16:59
Charles R
825213
answered Nov 22 at 16:59
Charles R
825213
answered Nov 22 at 16:59
Charles R
825213
answered Nov 22 at 16:59
Charles R
825213
825213
Thanks. How do I then plot the resulting DiGraph?
– prmlmu
Nov 23 at 17:20
add a comment |
Thanks. How do I then plot the resulting DiGraph?
– prmlmu
Nov 23 at 17:20
Thanks. How do I then plot the resulting DiGraph?
– prmlmu
Nov 23 at 17:20
Thanks. How do I then plot the resulting DiGraph?
– prmlmu
Nov 23 at 17:20
add a comment |
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