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)

Color coding Tree map with PLOTLY

My requirement is to plot a Tree map using python and I am using plotly for the same...
The Data frame which is close to my real time data is as follows
import pandas as pd
import plotly.express as px
data_frame = pd.DataFrame({'region':['AA','AB','AC','AD','AE'],
'number':[2,12,6,11,30],
'percentage':[94.03,91.23,95.66,97.99,99.22]})
And the plot from the following code, looks something like this
fig = px.treemap(data_frame, path= [data_frame['region']],
values=data_frame['number'],color=data_frame['percentage'])
fig.show()
The PLOT
BUT, i would like to have the color coding based on the column "percentage" with the custom scale as follows
data_frame['percentage'] > 98 : green (#00ff00)
data_frame['percentage'] between 95 - 98 : amber (#ffbf00)
data_frame['percentage'] < 95 red (#ff0000)
To be clear, I would only need the 3 colors mentioned above in my graph. These colors should be assigned based on the percentage values.
How can i achieve this?

I think you have to add new columns to facilitate color matching. Please refer below code:
import pandas as pd
import plotly.express as px
import numpy as np
data_frame = pd.DataFrame({'region':['AA','AB','AC','AD','AE'],
'number':[2,12,6,11,30],
'percentage':[94.03,91.23,95.66,97.99,99.22]})
condition = [data_frame['percentage']>98,
(data_frame['percentage']>95)&(data_frame['percentage']<98),
data_frame['percentage']<95]
choices = ['A','B','C']
data_frame['Condition'] = np.select(condition,choices,default='D')
fig = px.treemap(data_frame, path= [data_frame['region']],
values=data_frame['number'],color=data_frame['Condition'],
color_discrete_map={'A':'#00ff00',
'B':'#ffbf00',
'C':'#ff0000',
'D':'#AB63FA'})
fig.show()
So graph will be showed like below:

Can I make a pie chart based on indexes in Python?

Could you please help me if you know how to make a pie chart in Python from it?
This is a reproducible example how the df looks like. However, I have way more rows over there.
import pandas as pd
data = [["70%"], ["20%"], ["10%"]]
example = pd.DataFrame(data, columns = ['percentage'])
example.index = ['Lasiogl', 'Centella', 'Osmia']
example

You can use matplotlib to plot the pie chart using dataframe and its indexes as labels of the chart:
import matplotlib.pyplot as plt
import pandas as pd
data = ['percentage':["70%"], ["20%"], ["10%"]]
example = pd.DataFrame(data, columns = ['percentage'])
my_labels = 'Lasiogl', 'Centella', 'Osmia'
plt.pie(example,labels=my_labels,autopct='%1.1f%%')
plt.show()

Plotly graph_objects add df column to hovertemplate

I am trying to generally recreate this graph and struggling with adding a column to the hovertemplate of a plotly Scatter. Here is a working example:
import pandas as pd
import chart_studio.plotly as py
import plotly.graph_objects as go
dfs = pd.read_html('https://coronavirus.jhu.edu/data/mortality', header=0)
df = dfs[0]
percent = df['Case-Fatality'] # This is my closest guess, but isn't working
fig = go.Figure(data=go.Scatter(x=df['Confirmed'],
y = df['Deaths'],
mode='markers',
hovertext=df['Country'],
hoverlabel=dict(namelength=0),
hovertemplate = '%{hovertext}<br>Confirmed: %{x}<br>Fatalities: %{y}<br>%{percent}',
))
fig.show()
I'd like to get the column Cast-Fatality to show under {percent}
I've also tried putting in the Scatter() call a line for text = [df['Case-Fatality']], and switching {percent} to {text} as shown in this example, but this doesn't pull from the dataframe as hoped.
I've tried replotting it as a px, following this example but it throws the error dictionary changed size during iteration and I think using go may be simpler than px but I'm new to plotly.
Thanks in advance for any insight for how to add a column to the hover.

As the question asks for a solution with graph_objects, here are two that work-
Method (i)
Adding %{text} where you want the variable value to be and passing another variable called text that is a list of values needed in the go.Scatter() call. Like this-
percent = df['Case-Fatality']
hovertemplate = '%{hovertext}<br>Confirmed: %{x}<br>Fatalities: %{y}<br>%{text}',text = percent
Here is the complete code-
import pandas as pd
import plotly.graph_objects as go
dfs = pd.read_html('https://coronavirus.jhu.edu/data/mortality', header=0)
df = dfs[0]
percent = df['Case-Fatality'] # This is my closest guess, but isn't working
fig = go.Figure(data=go.Scatter(x=df['Confirmed'],
y = df['Deaths'],
mode='markers',
hovertext=df['Country'],
hoverlabel=dict(namelength=0),
hovertemplate = '%{hovertext}<br>Confirmed: %{x}<br>Fatalities: %{y}<br>%{text}',
text = percent))
fig.show()
Method (ii)
This solution requires you to see the hoverlabel as when you pass x unified to hovermode. All you need to do then is pass an invisible trace with the same x-axis and the desired y-axis values. Passing mode='none' makes it invisible. Here is the complete code-
import pandas as pd
import plotly.graph_objects as go
dfs = pd.read_html('https://coronavirus.jhu.edu/data/mortality', header=0)
df = dfs[0]
percent = df['Case-Fatality'] # This is my closest guess, but isn't working
fig = go.Figure(data=go.Scatter(x=df['Confirmed'],
y = df['Deaths'],
mode='markers',
hovertext=df['Country'],
hoverlabel=dict(namelength=0)))
fig.add_scatter(x=df.Confirmed, y=percent, mode='none')
fig.update_layout(hovermode='x unified')
fig.show()

The link you shared is broken. Are you looking for something like this?
import pandas as pd
import plotly.express as px
px.scatter(df,
x="Confirmed",
y="Deaths",
hover_name="Country",
hover_data={"Case-Fatality":True})
Then if you need to use bold or change your hover_template you can follow the last step in this answer

Drawing inspiration from another SO question/answer, I find that this is working as desired and permits adding multiple cols to the hover data:
import pandas as pd
import plotly.express as px
fig = px.scatter(df,
x="Confirmed",
y="Deaths",
hover_name="Country",
hover_data=[df['Case-Fatality'], df['Deaths/100K pop.']])
fig.show()

Plotly: How to make line charts colored by a variable using plotly.graph_objects?

I'm making a line chart below. I want to make the lines colored by a variable Continent. I know it can be done easily using plotly.express
Does anyone know how I can do that with plotly.graph_objects? I tried to add color=gapminder['Continent'], but it did not work.
Thanks a lot for help in advance.
import plotly.express as px
gapminder = px.data.gapminder()
import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Scatter(x=gapminder['year'], y=gapminder['lifeExp'],
mode='lines+markers'))
fig.show()

Using an approach like color=gapminder['Continent'] normally applies to scatterplots where you define categories to existing points using a third variable. You're trying to make a line plot here. This means that not only will you have a color per continent, but also a line per continent. If that is in fact what you're aiming to do, here's one approach:
Plot:
Code:
import plotly.graph_objects as go
import plotly.express as px
# get data
df_gapminder = px.data.gapminder()
# manage data
df_gapminder_continent = df_gapminder.groupby(['continent', 'year']).mean().reset_index()
df = df_gapminder_continent.pivot(index='year', columns='continent', values = 'lifeExp')
df.tail()
# plotly setup and traces
fig = go.Figure()
for col in df.columns:
fig.add_trace(go.Scatter(x=df.index, y=df[col].values,
name = col,
mode = 'lines'))
# format and show figure
fig.update_layout(height=800, width=1000)
fig.show()