Title: Graph Element
Dependencies: Matplotlib
Backends: Bokeh; Matplotlib

In [1]:

import pandas as pd
import holoviews as hv
from holoviews import opts, dim
from bokeh.sampledata.les_mis import data
import numpy as np

hv.extension('bokeh')
hv.output(size=200)

The Chord element allows representing the inter-relationships between data points in a graph. The nodes are arranged radially around a circle with the relationships between the data points drawn as arcs (or chords) connecting the nodes. The number of chords is scaled by a weight declared as a value dimension on the Chord element.

If the weight values are integers, they define the number of chords to be drawn between the source and target nodes directly. If the weights are floating point values, they are normalized to a default of 500 chords, which are divided up among the edges. Any non-zero weight will be assigned at least one chord.

The Chord element is a type of Graph element and shares the same constructor. The most basic constructor accepts a columnar dataset of the source and target nodes and an optional value. Here we supply a dataframe containing the number of dialogues between characters of the Les Misérables musical. The data contains source and target node indices and an associated value column:

In [2]:

italy_diet = pd.read_pickle("data/processed/Italy_opt_diet.pkl")
italy = italy_diet.sum(axis=0)
france_diet = pd.read_pickle("data/processed/France_opt_diet.pkl")
france = france_diet.sum(axis=0)
uk_diet = pd.read_pickle("data/processed/United Kingdom_opt_diet.pkl")
uk = uk_diet.sum(axis=0)
spain_diet = pd.read_pickle("data/processed/Spain_opt_diet.pkl")
spain = spain_diet.sum(axis=0)
germany_diet = pd.read_pickle("data/processed/Germany_opt_diet.pkl")
germany = germany_diet.sum(axis=0)

In [3]:

links_it = pd.DataFrame(italy).reset_index()
links_it["source"]="Italy"
links_it = links_it.rename(columns={"index":"target", 0:"value"})
links_it = links_it[["source", "target", "value"]]
links_fr = pd.DataFrame(france).reset_index()
links_fr["source"]="France"
links_fr = links_fr.rename(columns={"index":"target", 0:"value"})
links_fr = links_fr[["source", "target", "value"]]
links_uk = pd.DataFrame(uk).reset_index()
links_uk["source"]="United Kingdom"
links_uk = links_uk.rename(columns={"index":"target", 0:"value"})
links_uk = links_uk[["source", "target", "value"]]
links_ge = pd.DataFrame(germany).reset_index()
links_ge["source"]="Germany"
links_ge = links_ge.rename(columns={"index":"target", 0:"value"})
links_ge = links_ge[["source", "target", "value"]]
links_es = pd.DataFrame(spain).reset_index()
links_es["source"]="Spain"
links_es = links_es.rename(columns={"index":"target", 0:"value"})
links_es = links_es[["source", "target", "value"]]
links = links_it.append(links_fr).append(links_uk).append(links_ge).append(links_es)

In [4]:

tot_eu = links.groupby("source").sum().reset_index().rename(columns={"source":"name"})
tot_af = links.groupby("target").sum().reset_index().rename(columns={"target":"name"})
tot = tot_eu.append(tot_af)
tot.head()

Out[4]:

	name	value
0	France	102881.879243
1	Germany	112066.319546
2	Italy	92060.460720
3	Spain	86235.003277
4	United Kingdom	101507.471800

In [5]:

from sklearn.preprocessing import OrdinalEncoder
enc_eu = OrdinalEncoder(dtype=int)
eu_nations = links.source.values.reshape(-1,1)
enc_eu.fit(eu_nations)
enc_af = OrdinalEncoder(dtype=int)
af_nations = links.target.values.reshape(-1,1)
enc_af.fit(af_nations)
links[["source"]] = enc_eu.transform(links[["source"]])
links[["target"]] = enc_af.transform(links[["target"]]) + 10
links

Out[5]:

	source	target	value
0	2	17	25370.332652
1	2	19	10560.449765
2	2	32	8647.405612
3	2	22	7861.041846
4	2	33	6072.955554
...	...	...	...
20	3	11	260.635343
21	3	18	213.509272
22	3	16	163.345226
23	3	20	61.625137
24	3	15	59.402224

125 rows × 3 columns

In [6]:

def find_name(x):
    if (x<=4):
        return enc_eu.inverse_transform(np.array(x).reshape(-1,1)).flatten()[0]
    else:
        return enc_af.inverse_transform(np.array(x-10).reshape(-1,1)).flatten()[0]

In [7]:

def find_group(x):
    if (x<=4):
        return "Europe"
    else:
        return "Africa"

In [8]:

nodes_pd = pd.DataFrame(columns=["index", "name", "group"])
nodes_pd["index"] = list(links.source.values) + list(links.target.values)
nodes_pd["name"] = nodes_pd["index"].apply(lambda x: find_name(x))
nodes_pd["group"] = nodes_pd["index"].apply(lambda x: find_group(x))
nodes_pd = nodes_pd.groupby("name").first().reset_index()[["index", "name", "group"]]
nodes_pd = nodes_pd.sort_values("index")
nodes_pd = nodes_pd.merge(tot, on="name")
nodes_pd.replace({"United Republic of Tanzania":'Tanzania'}, inplace=True)
nodes_pd.replace({"Central African Republic":'Centr. Afr. Rep.'}, inplace=True)
nodes = hv.Dataset(nodes_pd, "index")
nodes.data.head()

Out[8]:

	index	name	group	value
0	0	France	Europe	102881.879243
1	1	Germany	Europe	112066.319546
2	2	Italy	Europe	92060.460720
3	3	Spain	Europe	86235.003277
4	4	United Kingdom	Europe	101507.471800

In [9]:

# nodes = hv.Dataset(pd.DataFrame(data['nodes']), 'index')
# nodes.data.name

Additionally we can now color the nodes and edges by their index and add some labels. The labels, node_color and edge_color options allow us to reference dimension values by name.

In [10]:

from math import pi
#0.019
def rotate_label(plot, element):
    text_cds = plot.handles['text_1_source']
    length = len(text_cds.data['angle'])
    text_cds.data['angle'] = [pi/256]*length
    xs = text_cds.data['x']
    ys = text_cds.data['y']
    text = np.array(text_cds.data['text'])
    xs[xs<0] -= np.array([len(t)*0.0275 for t in text[xs<0]])
    xs[xs>0] += np.array([len(t)*0.0035 for t in text[xs>0]])
    xs[np.where(text=="Botswana")] -= 0.02
    xs[np.where(text=="Centr. Afr. Rep.")] += 0.1
    ys[np.where(text=="Centr. Afr. Rep.")] -= 0.02
    xs[np.where(text=="Chad")] -= 0.02
    ys[np.where(text=="Angola")] += 0.01
    ys[np.where(text=="Eswatini")] -= 0.02
    xs[np.where(text=="Eswatini")] += 0.03
    xs[np.where(text=="Ethiopia")] += 0.035
    xs[np.where(text=="Congo")] -= 0.03
    ys[np.where(text=="Congo")] += 0.01
    xs[np.where(text=="Djibouti")] += 0.03
    xs[np.where(text=="Liberia")] += 0.175
    ys[np.where(text=="Liberia")] -= 0.02
    ys[np.where(text=="Lesotho")] -= 0.02
    xs[np.where(text=="Lesotho")] += 0.01
    move_up = ['Rwanda', 'Senegal', 'Sierra Leone', 'Sudan', 'Togo', 'Uganda']
    ys[[np.where(text==c)[0][0] for c in move_up]] +=0.025
    move_left = ['Madagascar', 'Malawi', 'Mozambique', 'Sierra Leone']
    xs[[np.where(text==c)[0][0] for c in move_left]] -=0.035
    move_down = ['Madagascar', 'Malawi', 'Mozambique']
    ys[[np.where(text==c)[0][0] for c in move_down]] -=0.01
    move_left2 = ['Tanzania', 'Zambia', 'Zimbabwe']
    xs[[np.where(text==c)[0][0] for c in move_left2]] -=0.025
    xs[np.where(text=="Namibia")] -= 0.01
    xs[np.where(text=="Uganda")] -= 0.01
    
from bokeh.models import HoverTool
hover = HoverTool(
    tooltips=[
        ( 'Country',   '@name'            ),
        ( 'Group',  '@group' ), # use @{ } for field names with spaces
        ( 'Import/Export', '@value tons'),
    ],
)

chord = hv.Chord((links, nodes))
chord.opts(
    opts.Chord(cmap='Dark2', edge_cmap='Dark2', edge_color=dim('source').str(), node_size=12, edge_alpha=0.15,\
               labels='name', node_color=dim('index').str(), edge_hover_line_color=None, node_hover_line_color=None, node_hover_fill_color=None,\
                edge_selection_line_color=None, tools=[hover, 'tap'], bgcolor='rgba(0,0,0,0)', border=0,finalize_hooks=[rotate_label] ))

Out[10]:

In [11]:

from bokeh.models import HoverTool
hover = HoverTool(
    tooltips=[
        ( 'Country',   '@name'            ),
        ( 'Group',  '@group' ), # use @{ } for field names with spaces
        ( 'Import/Export', '@value tons'),
    ],
)

options = dict(cmap='Dark2', edge_cmap='Dark2', edge_color=dim('source').str(), node_size=12, edge_alpha=0.15,\
               labels='name', node_color=dim('index').str(), edge_hover_line_color=None, node_hover_line_color=None, node_hover_fill_color=None,\
                edge_selection_line_color=None, tools=[hover, 'tap'], bgcolor='rgba(0,0,0,0)', border=0, finalize_hooks=[rotate_label])
chord = hv.Chord((links, nodes)).options(**options)
hv.renderer('bokeh').save(chord, 'docs/_includes/chord')

In [12]:

tot_it = links_it.groupby("source").sum().reset_index().rename(columns={"source":"name"})
tot_it = tot_it.append(links_it[["target", "value"]].rename(columns={"target":"name"}))
tot_it.replace({"United Republic of Tanzania":'Tanzania'}, inplace=True)
tot_it.replace({"Central African Republic":'Centr. Afr. Rep.'}, inplace=True)
tot_it.head()

Out[12]:

	name	value
0	Italy	92060.460720
0	Ethiopia	25370.332652
1	Kenya	10560.449765
2	Tanzania	8647.405612
3	Madagascar	7861.041846

In [13]:

links_it[["source"]] = enc_eu.transform(links_it[["source"]])
links_it[["target"]] = enc_af.transform(links_it[["target"]]) + 10
links_it.head()

Out[13]:

	source	target	value
0	2	17	25370.332652
1	2	19	10560.449765
2	2	32	8647.405612
3	2	22	7861.041846
4	2	33	6072.955554

In [14]:

nodes_italy_pd = nodes.data.copy()
nodes_italy_pd = nodes_italy_pd[~(nodes_italy_pd.name.isin(["France", "Germany", "United Kingdom", "Spain"]))]
nodes_italy_pd.drop(columns="value", inplace=True)
nodes_italy_pd = nodes_italy_pd.merge(tot_it, on="name")
nodes_italy = hv.Dataset(nodes_italy_pd, "index")
nodes_italy.data

Out[14]:

	index	name	group	value
0	2	Italy	Europe	92060.460720
1	10	Angola	Africa	1464.021255
2	11	Botswana	Africa	280.365196
3	12	Centr. Afr. Rep.	Africa	1029.741680
4	13	Chad	Africa	4046.982613
5	14	Congo	Africa	1168.294970
6	15	Djibouti	Africa	65.672100
7	16	Eswatini	Africa	176.567587
8	17	Ethiopia	Africa	25370.332652
9	18	Guinea-Bissau	Africa	230.086981
10	19	Kenya	Africa	10560.449765
11	20	Lesotho	Africa	68.043698
12	21	Liberia	Africa	578.177169
13	22	Madagascar	Africa	7861.041846
14	23	Malawi	Africa	2931.827882
15	24	Mozambique	Africa	3320.666955
16	25	Namibia	Africa	503.050673
17	26	Rwanda	Africa	1382.734793
18	27	Senegal	Africa	2946.557394
19	28	Sierra Leone	Africa	1203.713639
20	29	Sudan	Africa	4985.309801
21	30	Togo	Africa	488.006793
22	31	Uganda	Africa	4587.075291
23	32	Tanzania	Africa	8647.405612
24	33	Zambia	Africa	6072.955554
25	34	Zimbabwe	Africa	2091.378821

In [15]:

from bokeh.models import HoverTool

def rotate_label2(plot, element):
    text_cds = plot.handles['text_1_source']
    length = len(text_cds.data['angle'])
    text_cds.data['angle'] = [pi/256]*length
    xs = text_cds.data['x']
    ys = text_cds.data['y']
    text = np.array(text_cds.data['text'])
    xs[xs<0] -= np.array([len(t)*0.0275 for t in text[xs<0]])
    xs[xs>0] += np.array([len(t)*0.0035 for t in text[xs>0]])
    xs[np.where(text=="Botswana")] -= 0.02
    xs[np.where(text=="Centr. Afr. Rep.")] += 0.1
    ys[np.where(text=="Centr. Afr. Rep.")] -= 0.02
    xs[np.where(text=="Chad")] -= 0.02
    ys[np.where(text=="Angola")] += 0.01
    ys[np.where(text=="Eswatini")] -= 0.04
    xs[np.where(text=="Eswatini")] += 0.04
    xs[np.where(text=="Ethiopia")] += 0.035
    xs[np.where(text=="Congo")] -= 0.03
    ys[np.where(text=="Congo")] += 0.025
    xs[np.where(text=="Djibouti")] += 0.03
    xs[np.where(text=="Liberia")] += 0.19
    ys[np.where(text=="Liberia")] -= 0.02
    ys[np.where(text=="Lesotho")] -= 0.02
    xs[np.where(text=="Lesotho")] += 0.01
    move_up = ['Rwanda', 'Senegal', 'Sierra Leone', 'Sudan', 'Togo', 'Uganda']
    ys[[np.where(text==c)[0][0] for c in move_up]] +=0.025
    move_left = ['Madagascar', 'Malawi', 'Mozambique', 'Sierra Leone']
    xs[[np.where(text==c)[0][0] for c in move_left]] -=0.03
    move_down = ['Madagascar', 'Malawi', 'Mozambique']
    ys[[np.where(text==c)[0][0] for c in move_down]] -=0.01
    move_left2 = ['Tanzania', 'Zambia', 'Zimbabwe']
    xs[[np.where(text==c)[0][0] for c in move_left2]] -=0.025
    xs[np.where(text=="Namibia")] -= 0.01
    xs[np.where(text=="Uganda")] -= 0.01
    
hover = HoverTool(
    tooltips=[
        ( 'Country',   '@name'            ),
        ( 'Group',  '@group' ), # use @{ } for field names with spaces
        ( 'Import/Export', '@value tons'),
    ],
)

chord_it = hv.Chord((links_it, nodes_italy))
chord_it.opts(
    opts.Chord(cmap='Dark2', edge_cmap='Dark2', edge_color=dim('target').str(), node_size=12, edge_alpha=0.15,\
               labels='name', node_color=dim('index').str(), edge_hover_line_color=None, node_hover_line_color=None, node_hover_fill_color=None,\
                edge_selection_line_color=None, tools=[hover, 'tap'], finalize_hooks=[rotate_label2]))

Out[15]:

In [16]:

from bokeh.models import HoverTool
hover = HoverTool(
    tooltips=[
        ( 'Country',   '@name'            ),
        ( 'Group',  '@group' ), # use @{ } for field names with spaces
        ( 'Import/Export', '@value tons'),
    ],
)

options = dict(cmap='Dark2', edge_cmap='Dark2', edge_color=dim('target').str(), node_size=12, edge_alpha=0.15,\
               labels='name', node_color=dim('index').str(), edge_hover_line_color=None, node_hover_line_color=None, node_hover_fill_color=None,\
                edge_selection_line_color=None, tools=[hover, 'tap'], bgcolor='rgba(0,0,0,0)', border=0, finalize_hooks=[rotate_label2])
chord_it = hv.Chord((links_it, nodes_italy)).options(**options)
hv.renderer('bokeh').save(chord_it, 'docs/_includes/chord_it')

In [17]:

tot_fr = links_fr.groupby("source").sum().reset_index().rename(columns={"source":"name"})
tot_fr = tot_fr.append(links_fr[["target", "value"]].rename(columns={"target":"name"}))
tot_fr.replace({"United Republic of Tanzania":'Tanzania'}, inplace=True)
tot_fr.replace({"Central African Republic":'Centr. Afr. Rep.'}, inplace=True)
tot_fr.head()

Out[17]:

	name	value
0	France	102881.879243
0	Ethiopia	28324.819373
1	Kenya	11793.007659
2	Tanzania	9657.535962
3	Madagascar	8779.742545

In [18]:

links_fr[["source"]] = enc_eu.transform(links_fr[["source"]])
links_fr[["target"]] = enc_af.transform(links_fr[["target"]]) + 10
links_fr.head()

Out[18]:

	target	value
0	17	28324.819373
1	19	11793.007659
2	32	9657.535962
3	22	8779.742545
4	33	6783.757422

In [19]:

nodes_fr_pd = nodes.data.copy()
nodes_fr_pd = nodes_fr_pd[~(nodes_fr_pd.name.isin(["Italy", "Germany", "United Kingdom", "Spain"]))]
nodes_fr_pd.drop(columns="value", inplace=True)
nodes_fr_pd = nodes_fr_pd.merge(tot_fr, on="name")
nodes_fr = hv.Dataset(nodes_fr_pd, "index")
nodes_fr.data

Out[19]:

	index	name	group	value
0	0	France	Europe	102881.879243
1	10	Angola	Africa	1638.947392
2	11	Botswana	Africa	317.668942
3	12	Centr. Afr. Rep.	Africa	1154.174607
4	13	Chad	Africa	4522.226832
5	14	Congo	Africa	1308.837337
6	15	Djibouti	Africa	78.013715
7	16	Eswatini	Africa	201.802899
8	17	Ethiopia	Africa	28324.819373
9	18	Guinea-Bissau	Africa	261.544934
10	19	Kenya	Africa	11793.007659
11	20	Lesotho	Africa	80.661057
12	21	Liberia	Africa	650.107186
13	22	Madagascar	Africa	8779.742545
14	23	Malawi	Africa	3277.414284
15	24	Mozambique	Africa	3711.463249
16	25	Namibia	Africa	566.245815
17	26	Rwanda	Africa	1548.209842
18	27	Senegal	Africa	3293.856380
19	28	Sierra Leone	Africa	1348.374095
20	29	Sudan	Africa	5569.652292
21	30	Togo	Africa	549.452800
22	31	Uganda	Africa	5125.115492
23	32	Tanzania	Africa	9657.535962
24	33	Zambia	Africa	6783.757422
25	34	Zimbabwe	Africa	2339.247133

In [20]:

from bokeh.models import HoverTool
hover = HoverTool(
    tooltips=[
        ( 'Country',   '@name'            ),
        ( 'Group',  '@group' ), # use @{ } for field names with spaces
        ( 'Import/Export', '@value tons'),
    ],
)

chord_fr = hv.Chord((links_fr, nodes_fr))
chord_fr.opts(
    opts.Chord(cmap='Dark2', edge_cmap='Dark2', edge_color=dim('target').str(), node_size=12, edge_alpha=0.15,\
               labels='name', node_color=dim('index').str(), edge_hover_line_color=None, node_hover_line_color=None, node_hover_fill_color=None,\
                edge_selection_line_color=None, tools=[hover, 'tap'], finalize_hooks=[rotate_label2]))

Out[20]:

In [21]:

from bokeh.models import HoverTool
hover = HoverTool(
    tooltips=[
        ( 'Country',   '@name'            ),
        ( 'Group',  '@group' ), # use @{ } for field names with spaces
        ( 'Import/Export', '@value tons'),
    ],
)

options = dict(cmap='Dark2', edge_cmap='Dark2', edge_color=dim('target').str(), node_size=12, edge_alpha=0.15,\
               labels='name', node_color=dim('index').str(), edge_hover_line_color=None, node_hover_line_color=None, node_hover_fill_color=None,\
                edge_selection_line_color=None, tools=[hover, 'tap'], bgcolor='rgba(0,0,0,0)', border=0, finalize_hooks=[rotate_label2])
chord_fr = hv.Chord((links_fr, nodes_fr)).options(**options)
hv.renderer('bokeh').save(chord_fr, 'docs/_includes/chord_fr')

In [22]:

tot_ge = links_ge.groupby("source").sum().reset_index().rename(columns={"source":"name"})
tot_ge = tot_ge.append(links_ge[["target", "value"]].rename(columns={"target":"name"}))
tot_ge.replace({"United Republic of Tanzania":'Tanzania'}, inplace=True)
tot_ge.replace({"Central African Republic":'Centr. Afr. Rep.'}, inplace=True)
links_ge[["source"]] = enc_eu.transform(links_ge[["source"]])
links_ge[["target"]] = enc_af.transform(links_ge[["target"]]) + 10

In [23]:

nodes_ge_pd = nodes.data.copy()
nodes_ge_pd = nodes_ge_pd[~(nodes_ge_pd.name.isin(["France", "Italy", "United Kingdom", "Spain"]))]
nodes_ge_pd.drop(columns="value", inplace=True)
nodes_ge_pd = nodes_ge_pd.merge(tot_ge, on="name")
nodes_ge = hv.Dataset(nodes_ge_pd, "index")
nodes_ge.data.head()

Out[23]:

	index	name	group	value
0	1	Germany	Europe	112066.319546
1	10	Angola	Africa	1787.136446
2	11	Botswana	Africa	348.906952
3	12	Centr. Afr. Rep.	Africa	1259.454702
4	13	Chad	Africa	4925.625179

In [24]:

from bokeh.models import HoverTool
hover = HoverTool(
    tooltips=[
        ( 'Country',   '@name'            ),
        ( 'Group',  '@group' ), # use @{ } for field names with spaces
        ( 'Import/Export', '@value tons'),
    ],
)

chord_ge = hv.Chord((links_ge, nodes_ge))
chord_ge.opts(
    opts.Chord(cmap='Dark2', edge_cmap='Dark2', edge_color=dim('target').str(), node_size=12, edge_alpha=0.15,\
               labels='name', node_color=dim('index').str(), edge_hover_line_color=None, node_hover_line_color=None, node_hover_fill_color=None,\
                edge_selection_line_color=None, tools=[hover, 'tap'], finalize_hooks=[rotate_label2]))

Out[24]:

In [25]:

from bokeh.models import HoverTool
hover = HoverTool(
    tooltips=[
        ( 'Country',   '@name'            ),
        ( 'Group',  '@group' ), # use @{ } for field names with spaces
        ( 'Import/Export', '@value tons'),
    ],
)

options = dict(cmap='Dark2', edge_cmap='Dark2', edge_color=dim('target').str(), node_size=12, edge_alpha=0.15,\
               labels='name', node_color=dim('index').str(), edge_hover_line_color=None, node_hover_line_color=None, node_hover_fill_color=None,\
                edge_selection_line_color=None, tools=[hover, 'tap'], bgcolor='rgba(0,0,0,0)', border=0, finalize_hooks=[rotate_label2])
chord_ge = hv.Chord((links_ge, nodes_ge)).options(**options)
hv.renderer('bokeh').save(chord_ge, 'docs/_includes/chord_ge')

In [26]:

tot_uk = links_uk.groupby("source").sum().reset_index().rename(columns={"source":"name"})
tot_uk = tot_uk.append(links_uk[["target", "value"]].rename(columns={"target":"name"}))
tot_uk.replace({"United Republic of Tanzania":'Tanzania'}, inplace=True)
tot_uk.replace({"Central African Republic":'Centr. Afr. Rep.'}, inplace=True)
links_uk[["source"]] = enc_eu.transform(links_uk[["source"]])
links_uk[["target"]] = enc_af.transform(links_uk[["target"]]) + 10

In [27]:

nodes_uk_pd = nodes.data.copy()
nodes_uk_pd = nodes_uk_pd[~(nodes_uk_pd.name.isin(["France", "Italy", "Germany", "Spain"]))]
nodes_uk_pd.drop(columns="value", inplace=True)
nodes_uk_pd = nodes_uk_pd.merge(tot_uk, on="name")
nodes_uk = hv.Dataset(nodes_uk_pd, "index")
nodes_uk.data.head()

Out[27]:

	index	name	group	value
0	4	United Kingdom	Europe	101507.471800
1	10	Angola	Africa	1616.749298
2	11	Botswana	Africa	312.960106
3	12	Centr. Afr. Rep.	Africa	1138.393266
4	13	Chad	Africa	4461.863870

In [28]:

from bokeh.models import HoverTool
hover = HoverTool(
    tooltips=[
        ( 'Country',   '@name'            ),
        ( 'Group',  '@group' ), # use @{ } for field names with spaces
        ( 'Import/Export', '@value tons'),
    ],
)

chord_uk = hv.Chord((links_uk, nodes_uk))
chord_uk.opts(
    opts.Chord(cmap='Dark2', edge_cmap='Dark2', edge_color=dim('target').str(), node_size=12, edge_alpha=0.15,\
               labels='name', node_color=dim('index').str(), edge_hover_line_color=None, node_hover_line_color=None, node_hover_fill_color=None,\
                edge_selection_line_color=None, tools=[hover, 'tap'], finalize_hooks=[rotate_label2]))

Out[28]:

In [29]:

from bokeh.models import HoverTool
hover = HoverTool(
    tooltips=[
        ( 'Country',   '@name'            ),
        ( 'Group',  '@group' ), # use @{ } for field names with spaces
        ( 'Import/Export', '@value tons'),
    ],
)

options = dict(cmap='Dark2', edge_cmap='Dark2', edge_color=dim('target').str(), node_size=12, edge_alpha=0.15,\
               labels='name', node_color=dim('index').str(), edge_hover_line_color=None, node_hover_line_color=None, node_hover_fill_color=None,\
                edge_selection_line_color=None, tools=[hover, 'tap'], bgcolor='rgba(0,0,0,0)', border=0, finalize_hooks=[rotate_label2])
chord_uk = hv.Chord((links_uk, nodes_uk)).options(**options)
hv.renderer('bokeh').save(chord_uk, 'docs/_includes/chord_uk')

In [30]:

tot_es = links_es.groupby("source").sum().reset_index().rename(columns={"source":"name"})
tot_es = tot_es.append(links_es[["target", "value"]].rename(columns={"target":"name"}))
tot_es.replace({"United Republic of Tanzania":'Tanzania'}, inplace=True)
tot_es.replace({"Central African Republic":'Centr. Afr. Rep.'}, inplace=True)
links_es[["source"]] = enc_eu.transform(links_es[["source"]])
links_es[["target"]] = enc_af.transform(links_es[["target"]]) + 10

In [31]:

nodes_es_pd = nodes.data.copy()
nodes_es_pd = nodes_es_pd[~(nodes_es_pd.name.isin(["France", "Italy", "United Kingdom", "Germany"]))]
nodes_es_pd.drop(columns="value", inplace=True)
nodes_es_pd = nodes_es_pd.merge(tot_es, on="name")
nodes_es = hv.Dataset(nodes_es_pd, "index")
nodes_es.data.head()

Out[31]:

	index	name	group	value
0	3	Spain	Europe	86235.003277
1	10	Angola	Africa	1370.083228
2	11	Botswana	Africa	260.635343
3	12	Centr. Afr. Rep.	Africa	963.030392
4	13	Chad	Africa	3791.108316

In [32]:

from bokeh.models import HoverTool
hover = HoverTool(
    tooltips=[
        ( 'Country',   '@name'            ),
        ( 'Group',  '@group' ), # use @{ } for field names with spaces
        ( 'Import/Export', '@value tons'),
    ],
)

chord_es = hv.Chord((links_es, nodes_es))
chord_es.opts(
    opts.Chord(cmap='Dark2', edge_cmap='Dark2', edge_color=dim('target').str(), node_size=12, edge_alpha=0.15,\
               labels='name', node_color=dim('index').str(), edge_hover_line_color=None, node_hover_line_color=None, node_hover_fill_color=None,\
                edge_selection_line_color=None, tools=[hover, 'tap'], finalize_hooks=[rotate_label2]))

Out[32]:

In [33]:

from bokeh.models import HoverTool
hover = HoverTool(
    tooltips=[
        ( 'Country',   '@name'            ),
        ( 'Group',  '@group' ), # use @{ } for field names with spaces
        ( 'Import/Export', '@value tons'),
    ],
)

options = dict(cmap='Dark2', edge_cmap='Dark2', edge_color=dim('target').str(), node_size=12, edge_alpha=0.15,\
               labels='name', node_color=dim('index').str(), edge_hover_line_color=None, node_hover_line_color=None, node_hover_fill_color=None,\
                edge_selection_line_color=None, tools=[hover, 'tap'], bgcolor='rgba(0,0,0,0)', border=0, finalize_hooks=[rotate_label2])
chord_es = hv.Chord((links_es, nodes_es)).options(**options)
hv.renderer('bokeh').save(chord_es, 'docs/_includes/chord_es')

In [ ]: