I was doing some funnel plot using plotly, however, when I wanted to show the texts outside the box there is no text in left side and there is text in only right side.
setup
from plotly import graph_objects as go
stages = ["Homepage visit", "Search page visit",
"Payment Page", "Payment Confirmation"]
fig = go.Figure()
fig.add_trace(go.Funnel(
name = 'Desktop',
y = stages,
x = [30100, 27090, 2860, 150],
textposition = "outside",
textinfo = "value+percent previous"))
fig.add_trace(go.Funnel(
name = 'Mobile',
orientation = "h",
y = stages,
x = [15100, 12080, 2718, 302],
textposition = "outside",
textinfo = "value+percent previous"))
fig.show()
output
required
I want to see all the numbers. I tried both 'inside' and 'outside' but I was unable to see ALL the numbers.
this is not it, but it is something in this path, try exploring constraintext and text formatting:
from plotly import graph_objects as go
stages = ["Homepage visit", "Search page visit",
"Payment Page", "Payment Confirmation"]
fig = go.Figure()
fig.add_trace(go.Funnel(
name = 'Desktop',
y = stages,
x = [30100, 27090, 2860, 150],
textposition = "inside",
textinfo = "value+percent previous"
, constraintext='outside'
,textfont=dict(
family="sans serif",
size=14,
color="black"
)
)
)
fig.add_trace(go.Funnel(
name = 'Mobile',
orientation = "h",
y = stages,
x = [15100, 12080, 2718, 302],
textposition = "auto",
textinfo = "value+percent previous"))
fig.show()
Related
I have made a scatter plot using matplotlib and Plotly. I want the height, width and the markers to be scatter as in matplotlib plot. Please see the attached plots.
I used the following code in Plotly
import plotly
import plotly.plotly as py
from plotly.graph_objs import Scatter
import plotly.graph_objs as go
trace1 = go.Scatter(
x=x1_tsne, # x-coordinates of trace
y=y1_tsne, # y-coordinates of trace
mode='markers ', # scatter mode (more in UG section 1)
text = label3,
opacity = 1,
textposition='top center',
marker = dict(size = 25, color = color_4, symbol = marker_list_2, line=dict(width=0.5)),
textfont=dict(
color='black',
size=18, #can change the size of font here
family='Times New Roman'
)
)
layout = {
'xaxis': {
'showticklabels': False,
'showgrid': False,
'zeroline': False,
'linecolor':'black',
'linewidth':2,
'mirror':True,
'autorange':False,
'range':[-40, 40][![enter image description here][1]][1]
},
'yaxis': {
'showticklabels': False,
'showgrid': False,
'zeroline': False,
'linecolor':'black',
'linewidth':2,
'mirror':True,
'autorange':False,
'range':[-40, 40]
}
}
data = [trace1]
fig = go.Figure(
data= data,
layout= layout)
py.iplot(fig)
I try to tune the range but did not help. In addition, I use Autorange that did not help. Could you please help me with this.
I want the image as
##update: This can be done by the following code. I am updating this in the question:
trace1 = go.Scatter(
x=x1_tsne, # x-coordinates of trace
y=y1_tsne, # y-coordinates of trace
mode='markers +text ', # scatter mode (more in UG section 1)
text = label3,
opacity = 1,
textposition='top center',
marker = dict(size = 25, color = color_4, symbol = marker_list_2, line=dict(width=0.5)),
textfont=dict(
color='black',
size=18, #can change the size of font here
family='Times New Roman'
)
)
data = [trace1]
layout = go.Layout(
autosize=False,
width=1000,
height=1000,
xaxis= go.layout.XAxis(linecolor = 'black',
linewidth = 1,
mirror = True),
yaxis= go.layout.YAxis(linecolor = 'black',
linewidth = 1,
mirror = True),
margin=go.layout.Margin(
l=50,
r=50,
b=100,
t=100,
pad = 4
)
)
fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='size-margins')
Have you considered to use
fig.update_layout(
autosize=False,
width=800,
height=800,)
and eventually reduce the size of your marker?
UPDATE
Full Code
import plotly.graph_objs as go
trace1 = go.Scatter(
x=x1_tsne, # x-coordinates of trace
y=y1_tsne, # y-coordinates of trace
mode='markers +text ', # scatter mode (more in UG section 1)
text = label3,
opacity = 1,
textposition='top center',
marker = dict(size = 12, color = color_4, symbol = marker_list_2, line=dict(width=0.5)),
textfont=dict(
color='black',
size=18, #can change the size of font here
family='Times New Roman'
)
)
data = [trace1]
layout = go.Layout(
autosize=False,
width=1000,
height=1000,
xaxis= go.layout.XAxis(linecolor = 'black',
linewidth = 1,
mirror = True),
yaxis= go.layout.YAxis(linecolor = 'black',
linewidth = 1,
mirror = True),
margin=go.layout.Margin(
l=50,
r=50,
b=100,
t=100,
pad = 4
)
)
fig = go.Figure(data=data, layout=layout)
I am trying to showcase a scatter plot as well as the data for the the plot side by side in jupyter. I wish to add a plotly button (dropdown) that will show the filtered data as well as the corresponding scatter plot. Is this possible WITHOUT USING ipywidgets, using plotly dropdowns?
I was able to build two separate plots for data and scatter plot with dropdowns but cannot combine them together. Following is the code I tried. Here the dropdown only interacts with the table, the scatter plot is not updating.
import plotly.express as px
import plotly.graph_objects as go
import numpy as np
import pandas as pd
df = px.data.iris()
species = sorted(set(df['species']))
#fig=go.Figure()
default_species = "setosa"
df_default = df[df['species']==default_species]
fig = make_subplots(
rows=1, cols=2,
shared_xaxes=True,
horizontal_spacing=0.02,
specs=[[{"type": "scatter"},{"type": "table"}]]
)
fig.add_trace(
go.Scatter(
x=df_default["sepal_length"],
y=df_default["sepal_width"],
mode="markers"
),
row=1, col=1
)
fig.add_trace(
go.Table(
header=dict(
values=["sepal<br>length","sepal<br>length","petal<br>length","petal<br>width","species","species<br>id"],
font=dict(size=10),
align="left"
),
cells=dict(
values=[df_default[k].tolist() for k in df_default.columns],
align = "left")
),
row=1, col=2
)
buttons = []
for s in species:
s_data = df[df['species']==s]
buttons.append(dict(
method='restyle',
label=s,
visible=True,
args=[
{'values':[["sepal<br>length","sepal<br>length","petal<br>length","petal<br>width","species","species<br>id"]],
'cells':[dict(values=[s_data[k].tolist() for k in s_data.columns],align = "left")]},
{'y':[s_data["sepal_width"]],
'x':[s_data['sepal_length']],
'type':'scatter',
'mode':'markers'}
]
))
#fig.update_layout(width=1500, height=500)
# some adjustments to the updatemenus
updatemenu = []
your_menu = dict()
updatemenu.append(your_menu)
updatemenu[0]['buttons'] = buttons
updatemenu[0]['direction'] = 'down'
updatemenu[0]['showactive'] = True
updatemenu[0]['active'] = species.index(default_species)
updatemenu[0]['x'] = 0
updatemenu[0]['xanchor'] = 'left'
updatemenu[0]['y'] = 1.2
updatemenu[0]['yanchor'] = 'top'
# add dropdown menus to the figure
fig.update_layout(showlegend=False,
updatemenus=updatemenu,
xaxis_title="Sepal_Length",
yaxis_title="Sepal_Width"
)
fig.show()
I do not want to use ipywidgets.
The code that worked for me: Editing hope it helps some one
## Create Combination of Scatter Plot and Plotly Tables with interactive Static HTML
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import numpy as np
import pandas as pd
df = px.data.iris()
species_list = sorted(set(df['species']))
# --- function ---
def make_multi_plot(df1, item_list):
fig = make_subplots(rows=1,
cols=2,
#shared_xaxes=True,
#vertical_spacing=0.2,
specs = [[{}, {"type": "table"}]]
)
for item_id in item_list:
#print('item_id:', item_id)
trace1 = go.Scatter(
x=df1.loc[df1.species.isin([item_id])].sepal_length,
y=df1.loc[df1.species.isin([item_id])].sepal_width,
mode='markers',
name = str(item_id)
)
fig.append_trace(trace1, 1, 1)
trace2 = go.Table(
columnorder = [1,2,3,4,5,6],
columnwidth = [2,2,2,2,4,2],
header=dict(
values = ["sepal<br>length","sepal<br>length","petal<br>length","petal<br>width","species","species<br>id"],
font = dict(size=10),
align = "left"
),
cells = dict(
values = [df1[df1.species.isin([item_id])][k].tolist() for k in df1[df1.species.isin([item_id])].columns[:]],
align = "left"
)
)
fig.append_trace(trace2,1,2)
Ld = len(fig.data)
#print(Ld)
Lc = len(item_list)
for k in range(2, Ld):
fig.update_traces(visible=False, selector=k)
def create_layout_button(k, item_id):
#print(k, item_id)
visibility = [False]*2*Lc
for tr in [2*k, 2*k+1]:
visibility[tr] = True
#print(visibility)
return dict(label = item_id,
method = 'restyle',
args = [{'visible': visibility,
'title': item_id
}])
#updatemenu[0]['x'] = 0
#updatemenu[0]['xanchor'] = 'left'
#updatemenu[0]['y'] = 1.2
#updatemenu[0]['yanchor'] = 'top'
fig.update_layout(
updatemenus=[go.layout.Updatemenu(
active=0,
buttons=[create_layout_button(k, item_id) for k, item_id in enumerate(item_list)],
x=0.5,
y=1.3
)],
#title='Model Raporu',
#template='plotly_dark',
#height=800
xaxis_title="Sepal_Length",
yaxis_title="Sepal_Width"
)
fig.show()
# --- main ---
make_multi_plot(df1=df, item_list=species_list)
x2016 = data[data.year == 2016].iloc[:20,:]
num_students_size = [float(each.replace(',', '.')) for each in x2016.num_students]
international_color = [float(each) for each in x2016.international]
trace1 = go.Scatter(
x = x2016.world_rank,
y = x2016.teaching,
mode = "markers",
marker=dict(
color = international_color,
size = num_students_size,
showscale = True
),
text = x2016.university_name
)
data5 = [trace1]
iplot(data5)
This gives bubble plot and it does not show labels . How to add labels please help]1
Your [data5] would be better suited as a go.Figure() object.
There is a good sequence here to follow: https://plotly.com/python/line-and-scatter/#bubble-scatter-plots
Here is the reference to figure labels:
https://plotly.com/python/figure-labels/
fig.update_layout(
title="Plot Title",
xaxis_title="x Axis Title",
yaxis_title="y Axis Title",
font=dict(
family="Courier New, monospace",
size=18,
color="#7f7f7f"
)
)
fig.show()
Additional relevant help and tutorials here:
https://plotly.com/python/line-and-scatter/
So - to give a generic hint here, something like the following should work:
data5 = go.Figure(data=trace1,
title="Plot Title",
xaxis_title="x Axis Title",
yaxis_title="y Axis Title"
)
iplot(data5)
I am building a dashboard using Potly Dashboard. I am using a dark bootstrap theme therefore I don't want a white background.
However, my map now looks like this:
And the code that produced it is shown below:
trace_map = html.Div(
[
dcc.Graph(
id = "map",
figure = go.Figure(
data=go.Choropleth(
locations=code, # Spatial coordinates
z = df.groupby(['month']).sum()['Sales'].astype(int),
locationmode = 'USA-states',
colorscale = 'Reds',
colorbar_title = "USD",
), layout = go.Layout(title = 'The Cities Sold the Most Product',
font = {"size": 9, "color":"White"},
titlefont = {"size": 15, "color":"White"},
geo_scope='usa',
margin={"r":0,"t":40,"l":0,"b":0},
paper_bgcolor='#4E5D6C',
plot_bgcolor='#4E5D6C',
)
)
)
]
)
I have tried paper_bgcolor, and plot_bgcolor but couldn't make it work.
Ideally I would like to achieve how this image looks (please ignore the red dots):
Generally:
fig.update_layout(geo=dict(bgcolor= 'rgba(0,0,0,0)'))
And in your specific example:
go.Layout(geo=dict(bgcolor= 'rgba(0,0,0,0)')
Plot:
Code:
import plotly.graph_objects as go
fig = go.Figure(
data=go.Choropleth(
#locations=code, # Spatial coordinates
#z = df.groupby(['month']).sum()['Sales'].astype(int),
locationmode = 'USA-states',
colorscale = 'Reds',
colorbar_title = "USD",
), layout = go.Layout(geo=dict(bgcolor= 'rgba(0,0,0,0)'),
title = 'The Cities Sold the Most Product',
font = {"size": 9, "color":"White"},
titlefont = {"size": 15, "color":"White"},
geo_scope='usa',
margin={"r":0,"t":40,"l":0,"b":0},
paper_bgcolor='#4E5D6C',
plot_bgcolor='#4E5D6C',
)
)
fig.show()
And you might want to change the color of the lakes too. But do note that setting lakecolor = 'rgba(0,0,0,0)' will give the lakes the same color as the states and not the bakground. So I'd go with lakecolor='#4E5D6C'. You could of course do the same thing with bgcolor, but setting it to 'rgba(0,0,0,0)' gets rid of the white color which you specifically asked for.
Lake color plot:
Lake color code:
import plotly.graph_objects as go
fig = go.Figure(
data=go.Choropleth(
#locations=code, # Spatial coordinates
#z = df.groupby(['month']).sum()['Sales'].astype(int),
locationmode = 'USA-states',
colorscale = 'Reds',
colorbar_title = "USD",
), layout = go.Layout(geo=dict(bgcolor= 'rgba(0,0,0,0)', lakecolor='#4E5D6C'),
title = 'The Cities Sold the Most Product',
font = {"size": 9, "color":"White"},
titlefont = {"size": 15, "color":"White"},
geo_scope='usa',
margin={"r":0,"t":40,"l":0,"b":0},
paper_bgcolor='#4E5D6C',
plot_bgcolor='#4E5D6C',
)
)
fig.show()
And we could just as well change the state border colors, or what is more cryptically known as subunitcolor in this context. And to better match your desired endresult we could spice up the landcolor as well:
State border and state colors, plot:
State border and state colors, code:
import plotly.graph_objects as go
fig = go.Figure(
data=go.Choropleth(
#locations=code, # Spatial coordinates
#z = df.groupby(['month']).sum()['Sales'].astype(int),
locationmode = 'USA-states',
colorscale = 'Reds',
colorbar_title = "USD",
), layout = go.Layout(geo=dict(bgcolor= 'rgba(0,0,0,0)', lakecolor='#4E5D6C',
landcolor='rgba(51,17,0,0.2)',
subunitcolor='grey'),
title = 'The Cities Sold the Most Product',
font = {"size": 9, "color":"White"},
titlefont = {"size": 15, "color":"White"},
geo_scope='usa',
margin={"r":0,"t":40,"l":0,"b":0},
paper_bgcolor='#4E5D6C',
plot_bgcolor='#4E5D6C',
)
)
fig.show()
I found my way here because I wanted to change the theme of my Choroplethmapbox. The accepted solution helped, but ultimately I found the code below worked for my situation:
instantiate figure
fig = go.Figure()
add some traces
fig.add_trace(go.Choroplethmapbox(geojson=data_for_choropleth_geojson,
locations=data_for_choropleth['fips'],
z=data_for_choropleth['total_population'],
featureidkey='properties.fips'
))
finally, change the theme using update_layout
fig.update_layout(
hovermode='closest',
mapbox=dict(
# style options: "basic", "streets", "outdoors",
# "dark", "satellite", or "satellite-streets","light"
# "open-street-map", "carto-positron",
# "carto-darkmatter", "stamen-terrain",
# "stamen-toner" or "stamen-watercolor"
style='light',
bearing=0,
pitch=0,
accesstoken=TOKEN,
zoom=5,
center=dict(
lat=29.4652568,
lon=-98.613121
)
)
I have a dataframe like this:
id|course|sem
1|a|1
2|b|2
3|c|2
1|b|2
I want to plot a sankey diagram for semester to semester transition using plotly.(for eg.,sem1->sem2->sem3). The flow indicates the count of students taking a particular subject from one semester to other semester.How can I do it?
I have tried the following code:
data_trace = dict(
type='sankey',
domain = dict(
x = [0,1],
y = [0,1]
),
orientation = "h",
valueformat = ".0f",
node = dict(
pad = 10,
thickness = 30,
line = dict(
color = "black",
width = 0
),
label = df_sankey.index.dropna(how='any'),
#color = df_sankey['Color']
),
link = dict(
source = df_sankey.index.dropna( how='any'),
target = df_sankey.index.dropna( how='any'),
value = df_sankey['sem1'].dropna(axis=0, how='any'),
#color = df['Link Color'].dropna(axis=0, how='any'),
)
)
layout = dict(
title = "Student Semester Flow",
height = 772,
font = dict(
size = 10
),
)
fig7 = dict(data=[data_trace], layout=layout)
I did not get the expected output.This is the transition flow I am expecting
Sankey Diagram