def scatter3d(traces, columns, title, out_path):
data = []
for trace in traces:
data.append(
go.Scatter3d(
x=trace[columns[0]].values,
y=trace[columns[1]].values,
z=trace[columns[2]].values,
mode='markers',
marker=dict(
size=6,
#line=dict(
#color='rgba(217, 217, 217, 0.14)',
#width=5
#),
opacity=0.8)))
layout = go.Layout(
title=title,
#hovermode='closest',
scene=Scene(xaxis=XAxis(title=columns[0]),
yaxis=YAxis(title=columns[1]),
zaxis=ZAxis(title=columns[2])),
showlegend=True)
fig = go.Figure(data=data, layout=layout)
out_file = os.path.join(out_path, str(title) + ".html")
offpy(fig, filename=out_file, auto_open=True, show_link=False)
#with open("scatter3.txt", 'w') as fw:
# fw.write(offpy(fig, show_link=False, include_plotlyjs=False, output_type='div'))
return offpy(fig,
show_link=False,
include_plotlyjs=False,
output_type='div')
def scatter_by_cluster(traces, columns, title, axis_labels, out_path):
data = []
for trace in traces:
data.append(
go.Scatter(
x=trace[columns[0]].values,
y=trace[columns[1]].values,
name=trace[columns[2]].values[0],
mode="markers",
marker=dict(size=8,
# color='rgba(255, 182, 193, .9)',
)))
layout = go.Layout(title=title,
hovermode='closest',
xaxis=dict(
title=axis_labels[0],
ticklen=5,
zeroline=False,
gridwidth=2,
),
yaxis=dict(
title=axis_labels[1],
ticklen=5,
gridwidth=2,
),
showlegend=True)
fig = go.Figure(data=data, layout=layout)
out_file = os.path.join(out_path, str(title) + ".html")
offpy(fig, filename=out_file, auto_open=True, show_link=False)
return offpy(fig,
show_link=False,
include_plotlyjs=False,
output_type='div')
def top_words_prob_plot(all_top_words):
from plotly.subplots import make_subplots
fig = make_subplots(rows=len(all_top_words), cols=1)
for i, top_words in enumerate(all_top_words):
x = [x[0].strip('Ġ') for x in top_words]
y = [x[1] for x in top_words]
trace = go.Bar(
x=x,
y=y,
name=str(i)
)
fig.add_trace(trace, row=i+1, col=1)
fig.update_layout(
autosize=False,
width=500,
height=1000,
yaxis=dict(
title='Entropy',
titlefont_size=10,
tickfont_size=10,
),
)
offpy(fig, filename="top_words.html", auto_open=True, show_link=False)
def barchart(x, y):
assert len(x) == len(y), "the x and y should be the same length"
#x = [str(i)+" "+str(xi) for i, xi in enumerate(x)]
fig = go.Figure()
trace = go.Bar(
x=x,
y=y,
)
fig.add_trace(trace)
fig.update_layout(
title='',
xaxis_tickfont_size=23,
yaxis=dict(
title='KL-Divergence',
titlefont_size=20,
tickfont_size=20,
),
legend=dict(
x=0,
y=1.0,
bgcolor='rgba(255, 255, 255, 0)',
bordercolor='rgba(255, 255, 255, 0)'
),
barmode='group',
bargap=0.05, # gap between bars of adjacent location coordinates.
bargroupgap=0.1 # gap between bars of the same location coordinate.
)
offpy(fig, filename="barchart.html", auto_open=True, show_link=False)
def bar_chart_plot(x, y, title, out_path):
data = [go.Bar(x=x, y=y)]
layout = go.Layout(title=title)
fig = go.Figure(data=data, layout=layout)
out_file = os.path.join(out_path, str(title) + ".html")
offpy(fig, filename=out_file, auto_open=True, show_link=False)
def time_series_plot(x,y):
data = [go.Scatter(
x=x,
y=y)]
fig = go.Figure(data=data)
offpy(fig, filename="dd", auto_open=True, show_link=False)
def bar_chart_plot(x,y):
data = [go.Bar(
x=x,
y=y
)]
fig = go.Figure(data=data)
offpy(fig, filename="dd", auto_open=True, show_link=False)
def three_d_nework_graph(x_positions, y_positions, z_positions, colors, labels = "unknown"):
trace2=Scatter3d(x=x_positions,
y=y_positions,
z=z_positions,
mode='markers',
name='actors',
marker=Marker(symbol='dot',
size=6,
color=colors,
colorscale='Viridis',
line=Line(color='rgb(50,50,50)', width=0.5)
),
text=labels,
hoverinfo='text'
)
axis=dict(showbackground=True,
showline=True,
zeroline=True,
showgrid=True,
showticklabels=True,
title=''
)
layout = Layout(
title="Network of coappearances of documents in the whole repository(3D visualization)",
width=1000,
height=1000,
showlegend=False,
scene=Scene(
xaxis=XAxis(axis),
yaxis=YAxis(axis),
zaxis=ZAxis(axis),
),
margin=Margin(
t=100
),
hovermode='closest',
annotations=Annotations([
Annotation(
showarrow=False,
text="",
xref='paper',
yref='paper',
x=0,
y=0.1,
xanchor='left',
yanchor='bottom',
font=Font(
size=14
)
)
]), )
data=Data([trace2])
fig=Figure(data=data, layout=layout)
offpy(fig, filename="dd", auto_open=True, show_link=False)
def time_series_plot(x, y):
data = [go.Scatter(x=x, y=y)]
'''
layout = go.Layout(xaxis=dict(
range=[to_unix_time(datetime.datetime(2013, 10, 17)),
to_unix_time(datetime.datetime(2013, 11, 20))]
))
'''
fig = go.Figure(data=data)
offpy(fig, filename="dd", auto_open=True, show_link=False)
def visualize_topics(phi, words, num_topics, viz_threshold=9e-3):
phi_viz = np.transpose(phi)
words_to_display = ~np.all(phi_viz <= viz_threshold, axis=1)
words_viz = [words[i] for i in range(len(words_to_display)) if words_to_display[i]]
phi_viz = phi_viz[words_to_display]
trace = go.Heatmap(z=phi_viz,
x=['Topic ' + str(i) for i in range(1, num_topics + 1)],
y=words_viz)
data = [trace]
fig = go.Figure(data=data)
offpy(fig, filename="visualize_topics.html", auto_open=True, show_link=False)
def multi_barchart(x, y, z, names):
assert len(x) == len(y) == len(z), "the lengths should be the same"
#x = [str(i) + " " + str(xi) for i, xi in enumerate(x)]
fig = go.Figure()
fig.add_trace(go.Bar(
x=x,
y=y,
name=names[0]
))
fig.add_trace(go.Bar(
x=x,
y=z,
name=names[1]
))
fig.update_layout(
title='',
xaxis_tickfont_size=23,
yaxis=dict(
title='Entropy',
titlefont_size=20,
tickfont_size=20,
),
legend=dict(
x=0,
y=1.0,
bgcolor='rgba(255, 255, 255, 0)',
bordercolor='rgba(255, 255, 255, 0)',
font=dict(
family="sans-serif",
size=20,
color="black"
),
),
barmode='group',
bargap=0.05, # gap between bars of adjacent location coordinates.
bargroupgap=0.1 # gap between bars of the same location coordinate.
# legend = dict(
# x=0,
# y=1,
# traceorder="normal",
#
# bgcolor="LightSteelBlue",
# bordercolor="Black",
# borderwidth=2
# )
)
offpy(fig, filename="multi_barchart.html", auto_open=True, show_link=False)
def heamap(x, y, z, title, out_path="."):
trace = go.Heatmap(z=z, x=x, y=y, colorscale='Jet')
data = [trace]
layout = dict(yaxis=dict(tickmode="array"), )
fig = go.Figure(data=data, layout=layout)
out_file = os.path.join(out_path, str(title) + ".html")
offpy(fig, filename=out_file, auto_open=True, show_link=False)
return offpy(fig,
show_link=False,
include_plotlyjs=False,
output_type='div')
def scatter_plot(x, y, colors, names, output_file):
trace = go.Scatter(x=x,
y=y,
text=names,
mode='markers',
marker=dict(size=5,
color=colors,
line=dict(width=1, color='rgb(0, 0, 0)')))
data = [trace]
fig = go.Figure(data=data)
offpy(fig, filename=output_file + ".html", auto_open=True, show_link=False)
def stacked_bar_char(feature_counts_df, title, out_path):
data = []
feature_names = list(feature_counts_df.columns.values)
for index, row in feature_counts_df.iterrows():
counts = []
for feature_name in feature_names:
counts.append(row[feature_name])
trace = go.Bar(x=feature_names, y=counts, name=str(index))
data.append(trace)
layout = go.Layout(barmode='stack')
fig = go.Figure(data=data, layout=layout)
out_file = os.path.join(out_path, str(title) + ".html")
offpy(fig, filename=out_file, auto_open=True, show_link=False)
def boxplot(x_data, y_data, title, out_path="."):
traces = []
for xd, yd in zip(x_data, y_data):
traces.append(
go.Box(
y=yd,
name="_" + str(xd) + "_",
boxpoints='all',
jitter=0.5,
whiskerwidth=0.2,
#fillcolor=cls,
marker=dict(size=2, ),
line=dict(width=1),
))
layout = go.Layout(
title=title,
yaxis=dict(
autorange=True,
showgrid=True,
zeroline=True,
#dtick=5,
gridcolor='rgb(255, 255, 255)',
gridwidth=1,
zerolinecolor='rgb(255, 255, 255)',
zerolinewidth=2,
),
margin=dict(
l=40,
r=30,
b=80,
t=100,
),
#paper_bgcolor='rgb(243, 243, 243)',
#plot_bgcolor='rgb(243, 243, 243)',
showlegend=True,
)
fig = go.Figure(data=traces, layout=layout)
out_file = os.path.join(out_path, str(title) + ".html")
offpy(fig, filename=out_file, auto_open=True, show_link=False)
return offpy(fig,
show_link=False,
include_plotlyjs=False,
output_type='div')
def bar_chart_plot(x, y, title):
data = [ go.Bar(
x=x,
y=y
) ]
layout = go.Layout(title=title)
fig = go.Figure(data=data, layout=layout)
return offpy(fig,include_plotlyjs=False,show_link=False,output_type='div')
def scatter3d_plot(x, y, z, names, colors=None, output_file=None):
if colors is None:
colors = 'rgba(10, 10, 10, 0.9)'
trace = go.Scatter3d(x=x,
y=y,
z=z,
text=names,
mode='markers',
marker=dict(size=3,
color=colors,
line=dict(
color='rgba(217, 217, 217, 0.14)',
width=0.5),
opacity=1))
data = [trace]
fig = go.Figure(data=data)
offpy(fig, filename=output_file + ".html", auto_open=True, show_link=False)
def bar_chart_plot(x, y, text, info, title):
trace1 = go.Bar(
x=x,
y = y,
text = text,
name = info,
)
data = [ trace1 ]
layout = go.Layout(title=title)
fig = go.Figure(data=data, layout=layout)
return offpy(fig,include_plotlyjs=False,show_link=False,output_type='div')
def scatter(x, y, title, axis_labels, out_path):
trace = go.Scatter(x=x, y=y, mode='markers')
layout = go.Layout(title=title,
hovermode='closest',
xaxis=dict(
title=axis_labels[0],
ticklen=5,
zeroline=False,
gridwidth=2,
),
yaxis=dict(
title=axis_labels[1],
ticklen=5,
gridwidth=2,
),
showlegend=False)
data = [trace]
fig = go.Figure(data=data, layout=layout)
out_file = os.path.join(out_path, str(title) + ".html")
offpy(fig, filename=out_file, auto_open=True, show_link=False)
def frequency_trend_plot(x, y):
data = [go.Scatter(
x=x,
y=y,
line=dict(
color=('rgb(205, 12, 24)'),
width=4)
)]
layout = go.Layout(
title='Trend Over Time',
xaxis=dict(
title='Normalized Time'
),
yaxis=dict(
title='Frequency per month'
)
)
fig = go.Figure(data=data, layout=layout)
offpy(fig, filename="dd", auto_open=True, show_link=False)
def visualize_evolution(psi, phi, words, num_topics):
topic_words = []
for i in range(num_topics):
words_indices = np.argsort(phi[i, :])[:10]
topic_words.append([words[j] for j in words_indices])
xs = np.linspace(0, 1, num=1000)
data = []
for i in range(len(psi)):
ys = [
math.pow(1 - x, psi[i][0] - 1) * math.pow(x, psi[i][1] - 1) /
scipy.special.beta(psi[i][0], psi[i][1]) for x in xs
]
trace = go.Scatter(x=xs, y=ys, name=', '.join(topic_words[i]))
data.append(trace)
layout = go.Layout(
xaxis=dict(autorange=True,
showgrid=True,
zeroline=True,
showline=False,
autotick=True,
ticks='',
showticklabels=False),
yaxis=dict(autorange=True,
showgrid=True,
zeroline=True,
showline=False,
autotick=True,
ticks='',
showticklabels=False),
)
fig = go.Figure(data=data, layout=layout)
offpy(fig,
filename="visualize_evolution.html",
auto_open=True,
show_link=False)
def segments_plot(y, vertical_lines, title, out_path):
trace = go.Scatter(y=y, )
lines = []
for vertical_line in vertical_lines:
lines.append({
'type': 'line',
'x0': 0,
'y0': vertical_line,
'x1': len(y),
'y1': vertical_line,
'opacity': 0.7,
'line': {
'color': 'red',
'width': 2.5,
},
})
layout = {
'title': title,
'shapes': lines,
'yaxis': {
'title': "Value"
},
'xaxis': {
'title': "Sorted Index"
}
}
data = [trace]
fig = {
'data': data,
'layout': layout,
}
# fig = go.Figure(data=data, layout=layout)
out_file = os.path.join(out_path, str(title) + ".html")
offpy(fig, filename=out_file, auto_open=True, show_link=False)
def visualize_graph(G,
node_labels,
node_sizes=[],
edge_weights=[],
layout="graphviz",
filename="netwrokx",
title=""):
positions = reformat_graph_layout(G, layout)
edge_trace = Scatter(x=[],
y=[],
line=Line(width=[], color='rgba(136, 136, 136, .8)'),
hoverinfo='none',
mode='lines')
for edge in G.edges():
x0, y0 = positions[edge[0]]
x1, y1 = positions[edge[1]]
edge_trace['x'] += [x0, x1, None]
edge_trace['y'] += [y0, y1, None]
if edge_weights:
for weight in edge_weights:
edge_trace['line']['width'].append(weight)
else:
edge_trace['line']['width'] = [1] * len(G.edges())
node_trace = Scatter(
x=[],
y=[],
text=[],
mode='markers+text',
textfont=dict(family='Calibri (Body)', size=25, color='black'),
opacity=100,
# hoverinfo='text',
marker=Marker(
showscale=True,
# colorscale options
# 'Greys' | 'Greens' | 'Bluered' | 'Hot' | 'Picnic' | 'Portland' |
# Jet' | 'RdBu' | 'Blackbody' | 'Earth' | 'Electric' | 'YIOrRd' | 'YIGnBu'
colorscale='Jet',
reversescale=True,
color=[],
size=[],
colorbar=dict(thickness=15,
title='Node Connections',
xanchor='left',
titleside='right'),
line=dict(width=2)))
for node in G.nodes():
x, y = positions[node]
node_trace['x'].append(x)
node_trace['y'].append(y)
for adjacencies in G.adjacency_list():
node_trace['marker']['color'].append(len(adjacencies))
if not node_labels:
node_labels = G.nodes()
for node in node_labels:
node_trace['text'].append(node)
if node_sizes:
for size in node_sizes:
node_trace['marker']['size'].append(size)
else:
node_trace['marker']['size'] = [1] * len(G.nodes())
fig = Figure(
data=Data([edge_trace, node_trace]),
layout=Layout(
title='<br>' + title,
titlefont=dict(size=16),
showlegend=False,
width=1500,
height=800,
hovermode='closest',
margin=dict(b=20, l=350, r=5, t=200),
# family='Courier New, monospace', size=18, color='#7f7f7f',
annotations=[
dict(text="",
showarrow=False,
xref="paper",
yref="paper",
x=0.005,
y=-0.002)
],
xaxis=XAxis(showgrid=False, zeroline=False, showticklabels=False),
yaxis=YAxis(showgrid=False, zeroline=False, showticklabels=False)))
offpy(fig, filename=filename, auto_open=True, show_link=False)
def visualize_graph_3d(G, node_labels, node_sizes, filename, title="3d"):
edge_trace = Scatter3d(x=[],
y=[],
z=[],
mode='lines',
line=Line(color='rgba(136, 136, 136, .8)', width=1),
hoverinfo='none')
node_trace = Scatter3d(
x=[],
y=[],
z=[],
mode='markers',
#name='actors',
marker=Marker(
symbol='dot',
size=[],
color=[],
colorscale='Jet', #'Viridis',
colorbar=dict(thickness=15,
title='Node Connections',
xanchor='left',
titleside='right'),
line=Line(color='rgb(50,50,50)', width=0.5)),
text=[],
hoverinfo='text')
positions = nx.fruchterman_reingold_layout(G,
dim=3,
k=0.5,
iterations=1000)
for edge in G.edges():
x0, y0, z0 = positions[edge[0]]
x1, y1, z1 = positions[edge[1]]
edge_trace['x'] += [x0, x1, None]
edge_trace['y'] += [y0, y1, None]
edge_trace['z'] += [z0, z1, None]
for node in G.nodes():
x, y, z = positions[node]
node_trace['x'].append(x)
node_trace['y'].append(y)
node_trace['z'].append(z)
for adjacencies in G.adjacency_list():
node_trace['marker']['color'].append(len(adjacencies))
for size in node_sizes:
node_trace['marker']['size'].append(size)
for node in node_labels:
node_trace['text'].append(node)
axis = dict(showbackground=False,
showline=False,
zeroline=False,
showgrid=False,
showticklabels=False,
title='')
layout = Layout(
title=title,
width=1000,
height=1000,
showlegend=False,
scene=Scene(
xaxis=XAxis(axis),
yaxis=YAxis(axis),
zaxis=ZAxis(axis),
),
margin=Margin(t=100),
hovermode='closest',
annotations=Annotations([
Annotation(showarrow=False,
text="",
xref='paper',
yref='paper',
x=0,
y=0.1,
xanchor='left',
yanchor='bottom',
font=Font(size=14))
]),
)
data = Data([node_trace, edge_trace])
fig = Figure(data=data, layout=layout)
offpy(fig, filename=filename, auto_open=True, show_link=False)
def visualize(config, G, node_size):
keys = G.nodes()
values = range(len(G.nodes()))
dictionary = dict(zip(keys, values))
inv_map = {v: k for k, v in dictionary.items()}
G = nx.relabel_nodes(G, dictionary)
try:
pos = graphviz_layout(G)
except:
raise Exception("there is something wrong with graphviz")
edge_trace = go.Scatter(x=[],
y=[],
line=dict(width=0.8,
color='rgba(136, 136, 136, .9)'),
hoverinfo='none',
mode='lines')
for edge in G.edges():
x0, y0 = pos[edge[0]]
x1, y1 = pos[edge[1]]
edge_trace['x'] += (x0, x1, None)
edge_trace['y'] += (y0, y1, None)
# for weight in weights:
# print(weight)
# edge_trace['line']['width'].append(weight)
node_trace = go.Scatter(
x=[],
y=[],
text=[],
mode='markers+text',
textfont=dict(family='Calibri (Body)', size=14, color='black'),
opacity=1,
# hoverinfo='text',
marker=go.Marker(
showscale=True,
# colorscale options
# 'aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance',
# 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg',
# 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl',
# 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric',
# 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys',
# 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet',
# 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges',
# 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg',
# 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor',
# 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy',
# 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral',
# 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose',
# 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight',
# 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd'
colorscale=config.color_scale,
reversescale=True,
color=[],
size=[],
colorbar=dict(thickness=15,
title='Node Connections',
xanchor='left',
titleside='right'),
line=dict(width=1.7)))
for node in G.nodes():
x, y = pos[node]
node_trace['x'] += (x, )
node_trace['y'] += (y, )
for i, adjacencies in G.adjacency():
node_trace['marker']['color'] += (len(adjacencies), )
for node in G.nodes():
node_trace['text'] += (inv_map[node], )
for size in node_size:
node_trace['marker']['size'] += (abs(math.log(size)) * 10, )
fig = go.Figure(
data=[edge_trace, node_trace],
layout=go.Layout(
title='<br>' + config.title,
titlefont=dict(size=12),
showlegend=False,
width=1400,
height=800,
hovermode='closest',
margin=dict(b=20, l=350, r=5, t=200),
# family='Courier New, monospace', size=18, color='#7f7f7f',
annotations=[
dict(text="",
showarrow=False,
xref="paper",
yref="paper",
x=0.005,
y=-0.002)
],
xaxis=go.layout.XAxis(showgrid=False,
zeroline=False,
showticklabels=False),
yaxis=go.layout.YAxis(showgrid=False,
zeroline=False,
showticklabels=False)))
offpy(fig, filename=config.out_file_name, auto_open=True, show_link=False)
def visualize_3d(config, G, node_sizes):
keys = G.nodes()
values = range(len(G.nodes()))
dictionary = dict(zip(keys, values))
inv_map = {v: k for k, v in dictionary.items()}
G = nx.relabel_nodes(G, dictionary)
edge_trace = go.Scatter3d(x=[],
y=[],
z=[],
mode='lines',
line=go.scatter3d.Line(
color='rgba(136, 136, 136, .8)', width=1),
hoverinfo='none')
node_trace = go.Scatter3d(
x=[],
y=[],
z=[],
mode='markers',
#name='actors',
marker=go.scatter3d.Marker(
symbol='circle',
size=[],
color=[],
colorscale=config.color_scale, #'Viridis',
colorbar=dict(thickness=15,
title='Node Connections',
xanchor='left',
titleside='right'),
#line=go.Line(color='rgb(50,50,50)', width=0.5)
),
text=[],
hoverinfo='text')
positions = nx.fruchterman_reingold_layout(G,
dim=3,
k=0.5,
iterations=1000)
for edge in G.edges():
x0, y0, z0 = positions[edge[0]]
x1, y1, z1 = positions[edge[1]]
edge_trace['x'] += (
x0,
x1,
)
edge_trace['y'] += (
y0,
y1,
)
edge_trace['z'] += (
z0,
z1,
)
for node in G.nodes():
x, y, z = positions[node]
node_trace['x'] += (x, )
node_trace['y'] += (y, )
node_trace['z'] += (z, )
for i, adjacencies in G.adjacency():
node_trace['marker']['color'] += (len(adjacencies), )
for size in node_sizes:
node_trace['marker']['size'] += (abs(math.log(size)) * 10, )
for node in G.nodes():
node_trace['text'] += (inv_map[node], )
axis = dict(showbackground=False,
showline=False,
zeroline=False,
showgrid=False,
showticklabels=False,
title='')
layout = go.Layout(
title=config.title,
width=1000,
height=1000,
showlegend=False,
scene=go.Scene(
xaxis=go.XAxis(axis),
yaxis=go.YAxis(axis),
zaxis=go.ZAxis(axis),
),
margin=go.Margin(t=100),
hovermode='closest',
)
fig = go.Figure(data=[node_trace, edge_trace], layout=layout)
offpy(fig, filename=config.out_file_name, auto_open=True, show_link=False)
import plotly.plotly as py
from plotly.offline import iplot, plot as offpy
fig = py.get_figure('https://plot.ly/~jackp/8715', raw=True)
iplot(fig)
print(offpy(fig, filename='33.html', auto_open=True, show_link=False))
from plotly.offline import plot as offpy
import plotly.graph_objs as go
trace = go.Heatmap(
name='1st Trace',
z=[1, 2, 3],
x=[4, 5, 6],
y=[7, 8, 9],
colorscale='Jet',
)
data = [trace]
layout = dict(title='asdasdasdasd',
yaxis=dict(title='yyyyyyyy', tickmode="array"),
xaxis=dict(title='xxxxxxxxxxxx', tickmode="array"))
fig = go.Figure(data=data, layout=layout)
offpy(fig,
show_link=False,
include_plotlyjs=True,
filename='d3-world-map.html')
#
#
# import plotly.figure_factory as ff
# df = pd.read_excel("1.xlsx", names = ['Country', 'Share'],skiprows = [0])
# df['Share'] = pd.Series(["{0:.1}%".format(val * 100) for val in df['Share']], index = df.index)
# data = [ dict(
# type = 'choropleth',
# locations = df['Country'],
# z = df['Share'],
# text = df['Country'],
# colorscale = [[0,"rgb(5, 10, 172)"],[0.35,"rgb(40, 60, 190)"],[0.5,"rgb(70, 100, 245)"],\
# [0.6,"rgb(90, 120, 245)"],[0.7,"rgb(106, 137, 247)"],[1,"rgb(220, 220, 220)"]],
# autocolorscale = False,
# reversescale = True,
def visualize_associations(X, Y, Z, output_file):
trace = go.Heatmap(z=Z, x=X, y=Y)
data = [trace]
fig = go.Figure(data=data)
offpy(fig, filename=output_file + ".html", auto_open=True, show_link=False)
def bar_chart_plot(x, y, output_file):
data = [go.Bar(x=x, y=y)]
fig = go.Figure(data=data)
offpy(fig, filename=output_file + ".html", auto_open=True, show_link=False)
