Develop Reference

Outliers not showing up in plotly

Hi I am using this code to generate a boxplot:
However, it is not showing all the data points also not showing up the outliers on the top. I am using this code:
import plotly.express as px
fig = px.box(dataset, y= 'Report_used',hover_name='entity_name')
fig.show()
It needs to be like this:
How can I do this?
Thanks

import plotly.express as px
fig = px.box(dataset,
y= 'Report_used',
hover_name='entity_name',
points='all')
fig.update_traces(pointpos=0)
fig.show()
If you wanted all the points to be on the whisker line:
fig.update_traces(pointpos=0, jitter=0)

How to add a secondary Y axis to a Plotly Express bar plot?

I would like to add a second Y axis to my bar plot bellow, that is the number of citizens in integer:
this graph was made using plotly:
import plotly.express as px
fig = px.bar(df, x="country",y="pourcent_visit",color="city",barmode='group')
# fig.add_hline(y=10)
fig.show()

To my knowledge, there's no direct way to do this. But you can easily build a Plotly Express figure, grab the traces (and data structures) from there and combine them in a figure that allows multiple axes using fig = make_subplots(specs=[[{"secondary_y": True}]]). With no provided data sample, I'll use the built-in dataset px.data.tips() that I'm guessing to a large part resembles the structure of your real world dataset judging by the way you've applied the arguments in px.bar(). Details in the comments, but please don't hesitate to let me know if something is unclear.
Plot:
Complete code:
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
# sample data
df = px.data.tips()
# figure setup with multiple axes
fig = make_subplots(specs=[[{"secondary_y": True}]])
# build plotly express plot
fig2 = px.bar(df, x="day", y="total_bill", color="smoker", barmode="group")
# add traces from plotly express figure to first figure
for t in fig2.select_traces():
fig.add_trace(t, secondary_y = False)
# handle data for secondary axis
df2 = df.groupby('day').agg('sum')#.reset_index()
df2 = df2.reindex(index = df['day'].unique()).reset_index()
#
fig.add_trace(go.Scatter(x = df2['day'], y = df2['size'], mode = 'lines'), secondary_y = True)
# fix layout
fig.update_layout(legend_title_text = 'smoker')
fig.show()

Plotly: How to display the total sum of the values at top of a stacked bar chart along with the individual bar values?

I am trying to add the total at the top of the each stacked bar along with the individual bar values in Plotly Express in Python.
import plotly.express as px
df = px.data.medals_long()
fig = px.bar(df, x="medal", y="count", color="nation", text_auto=True)
fig.show()
This gives the below result
However I want the chart as below:

Although it can be annotated as a string, the easiest way is to add a graph in the text mode of a scatter plot.
import plotly.express as px
import plotly.graph_objects as go
df = px.data.medals_long()
dfs = df.groupby('medal').sum()
fig = px.bar(df, x="medal", y="count", color="nation", text_auto=True)
fig.add_trace(go.Scatter(
x=dfs.index,
y=dfs['count'],
text=dfs['count'],
mode='text',
textposition='top center',
textfont=dict(
size=18,
),
showlegend=False
))
fig.update_yaxes(range=[0,50])
fig.show()

How to update range_color in Plotly Express?

I am using plotly express and I want to display some data:
import plotly.express as px
dfx = px.data.tips()
fig = px.scatter(dfx,
x='total_bill', y='tip',
color='size',
template='plotly_dark',
range_color=[2,4])
My goal is to update the range color after it has been defined.
I tried something like this:
fig.update_layout(range_color=[3,6])
ValueError: Invalid property specified for object of type plotly.graph_objs.Layout: 'range'
but without success.
Are you aware of what I need to write in order to update the range color values?

To change the range of the color bar, you would change the maximum and minimum values of the color axis. This is different from the description of the graph settings, which can be found in fig.layout.
import plotly.express as px
dfx = px.data.tips()
fig = px.scatter(dfx,
x='total_bill', y='tip',
color='size',
template='plotly_dark',
range_color=[2,4])
fig.update_layout(coloraxis=dict(cmax=6, cmin=3))
fig.show()

I think you need to use range_color in the px.scatter function
import plotly.express as px
df = px.data.iris()
fig = px.scatter(df,
x="sepal_width",
y="sepal_length",
color="sepal_length",
color_continuous_scale=["red",
"green", "blue"])
fig.show()
Here is a link to the documentation plotly
You can also look here at fig.update_coloraxes
update coloraxes
Also just found this in the documentation for update_layout
fig.update_layout(colorscale=dict(...))
update colorscale

Highlight one specific bar in plotly bar chart [python]

I'm using a plotly.express bar chart to visualize categorical data like this:
fig = px.bar(data, x='Algorithm', y='NDE', text_auto='.3f', color='Algorithm',
color_discrete_map={'Ensembling':'orange', 'CO':'blue', 'Mean':'blue', 'DAE':'blue',
'S2P':'blue', 'S2S':'blue', 'WinGru':'blue'})
fig.update_layout(barmode='stack', xaxis={'categoryorder':'total descending'})
fig.show()
Gives me this result:
However, that way of highlighting a specific bar in the chart seems somewhat "overengineered" to me.
So my question is: Does anyone know a more simple way to highlight one specific bar in a python plotly express bar chart?
Thanks for any suggestions! :-)

No need to be that explicit with color_discrete_map. You can define a default color and then overwrite. This still generates the same kind of color_discrete_map dictionary as in your example, but it's more robust.
import plotly.express as px
default_color = "blue"
colors = {"China": "red"}
data = px.data.gapminder().query("year == 1952")
color_discrete_map = {
c: colors.get(c, default_color)
for c in data.country.unique()}
fig = px.bar(data, x='country', y='pop', color='country',
color_discrete_map=color_discrete_map)
fig.update_traces(showlegend=False)
fig.show()