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Adding text or cross sign on every subplot of plotly, each in unique positions of the subplots

I am struggling to put a cross sign in certain positions of each subplots of plotly in Python. I have 2 subplots and in each one, I want to out the cross in certain positions as below.
Position of the cross sign at the subplot_1 and 2 are attached.
import numpy as np
import plotly.graph_objs as go
import plotly.figure_factory as ff
from plotly.subplots import make_subplots
import string
#Define data for heatmap
N=5
x = np.array([10*k for k in range(N)])
y = np.linspace(0, 2, N)
z1 = np.random.randint(5,15, (N,N))
z2 = np.random.randint(10,27, (N,N))
mytext = np.array(list(string.ascii_uppercase))[:25].reshape(N,N)
fig1 = ff.create_annotated_heatmap(z1, x.tolist(), y.tolist(), colorscale='matter')
fig2 = ff.create_annotated_heatmap(z2, x.tolist(), y.tolist(), annotation_text=mytext, colorscale='Viridis')
fig = make_subplots(
rows=1, cols=2,
horizontal_spacing=0.05,
)
fig.add_trace(fig1.data[0], 1, 1)
fig.add_trace(fig2.data[0], 1, 2)
annot1 = list(fig1.layout.annotations)
annot2 = list(fig2.layout.annotations)
for k in range(len(annot2)):
annot2[k]['xref'] = 'x2'
annot2[k]['yref'] = 'y2'
fig.update_layout(annotations=annot1+annot2)

There are two ways to deal with this question: the first is to use the line mode of the scatterplot and the second is to add a shape. In the line mode of the scatterplot, the real starting position is -0.5, so the heatmap and the cross line are misaligned. So I chose to add a figure.
Also, I can now annotate without using figure_factory, so I'll use a graph object to construct the graph. The configuration is one heatmap combined with two shapes, with the y-axis and x-axis scales changed.
import numpy as np
import plotly.graph_objs as go
from plotly.subplots import make_subplots
np.random.seed(1)
fig = make_subplots(rows=1,
cols=2,
horizontal_spacing=0.05,
)
fig.add_trace(go.Heatmap(z=z1,
text=z1,
texttemplate='%{text}',
showscale=False,
),
row=1,col=1
)
fig.add_shape(type='line',
x0=1.5, y0=1.5, x1=2.5, y1=2.5,
line=dict(color='black', width=2)
)
fig.add_shape(type='line',
x0=2.5, y0=1.5, x1=1.5, y1=2.5,
line=dict(color='black', width=2)
)
fig.add_trace(go.Heatmap(z=z2,
text=mytext,
texttemplate='%{text}',
showscale=False,
colorscale = 'Viridis'
),
row=1,col=2
)
fig.add_shape(type='line',
x0=0.5, y0=-0.5, x1=1.5, y1=0.5,
line=dict(color='black', width=2),
row=1,col=2
)
fig.add_shape(type='line',
x0=1.5, y0=-0.5, x1=0.5, y1=0.5,
line=dict(color='black', width=2),
row=1, col=2
)
fig.update_yaxes(tickvals=[0,1,2,3,4], ticktext=y.tolist())
fig.update_xaxes(tickvals=[0,1,2,3,4], ticktext=x.tolist())
fig.update_layout(autosize=False, width=800)
fig.show()

How to add labels to plotly Box chart like Scatter chart?

I couldn't find the way to add text labels to plotly/dash box plot like you could add it to a scatterplot. In the example below, for ScatterPlot x=qty, y=price and you can then add Salesperson to the graph when the cursor is on Marker. For adding this I use the 'text' argument.
In the second example for BoxPlot when x=date, y=price I want to add salesperson in the same way. It would be very useful in case of outliers to see immediately who was the salesperson for that purchase. I looked in the documentation, but there is no clue. I assume it's not possible but still decided to try my luck here.
scatterplot:
import plotly.offline as pyo
import plotly.graph_objs as go
purchase={'date':['11/03/2021','12/03/2021','14/03/2021','11/03/2021'],
'price':[300, 400,200, 200],
'currency':['eur', 'usd','usd','usd'],
'qty':[200, 300, 400, 500],
'salesman':['AC', 'BC', "CC", 'DC']}
pur=pd.DataFrame(purchase)
pur
data = [go.Scatter(
x = pur['qty'],
y = pur['price'],
mode = 'markers',
text=pur['salesman'],
marker = dict(
size = 12,
color = 'rgb(51,204,153)',
symbol = 'pentagon',
line = dict(
width = 2,
)
)
)]
layout = go.Layout(
title = 'Random Data Scatterplot',
xaxis = dict(title = 'Some random x-values'),
yaxis = dict(title = 'Some random y-values'),
hovermode ='closest'
)
fig = go.Figure(data=data, layout=layout)
fig.show()
boxplot:
import plotly.offline as pyo
import plotly.graph_objs as go
x = pur['date']
y = pur['price']
data = [
go.Box(
y=y,
x=x,
text=pur['salesman']
)
]
layout = go.Layout(
title = 'box_plot'
)
fig = go.Figure(data=data, layout=layout)
fig.show()

The data you currently have is not suitable for boxplot. If you try to plot a boxplot with your data, the list [300, 400,200, 200] is used only once for the first date. For the other dates, there is no data.
I will show a simpler example with my own data.
dataset.csv
salesman,sales
alan,1.8
bary,2.3
copa,4.2
dac,1.19
eila,2.3
foo,2.5
gary,0.1
holland,10
code
import plotly.graph_objs as go
import pandas as pd
import plotly.io as pio
pio.renderers.default = 'browser'
df = pd.read_csv("deletelater")
fig = go.Figure()
fig.add_trace(go.Box(
y=df["sales"],
name='12/12/22',
customdata=df["salesman"],
hovertemplate='<b>sales: %{y}</b><br>salesperson: %{customdata}'
))
fig.show()
Diagram
As you can see, the name of the outlier salesperson is displayed on the hover label.

Draw multiple CSV files in a HTML page using Plotly

I want to draw multiple CSV files on an HTML page with fig = make_subplots(rows=.., cols=..).
df1 = pd.read_csv('first_input.csv')
fig1 = px.scatter(df, x="...", y="...", color="..")
df2 = pd.read_csv('first_input.csv')
fig2 = px.scatter(df, x="...", y="...", color="..")

Unfortunately plotly subplots do not directly support plotly.express figures as explained in the documentation here.
However, when you create a plotly.express figure using fig1 = px.scatter(df, x="...", y="...", color=".."), you are actually creating a figure where fig1.data is a tuple of go.Scatter traces. You can access each trace in fig1.data and add it to your subplots object.
If you have multiple px.scatter figures, you can iterate through them, and add each trace from px.scatter figure to your subplots object at the appropriate row and column. Then we can add the axes titles from each px.scatter figure to the subplots object layout.
I'll use the tips sample dataset to demonstrate:
import plotly.express as px
from plotly.subplots import make_subplots
df = px.data.tips()
fig1 = px.scatter(df, x="total_bill", y="tip", color="smoker")
fig2 = px.scatter(df, x="total_bill", y="tip", color="day")
fig_subplots = make_subplots(rows=2, cols=1)
for trace in fig1.data:
fig_subplots.add_trace(
trace,
row=1, col=1
)
for trace in fig2.data:
fig_subplots.add_trace(
trace,
row=2, col=1
)
## x and y axies in fig_subplots["layout"] are called xaxis, xaxis2, ..., yaxis, yaxis2, ...
## here we are making the assumption you are stacking your plots vertically
def modify_axis_titles(fig_subplots, px_fig, nrow):
xaxis_name, yaxis_name = f"xaxis{nrow}", f"yaxis{nrow}"
fig_subplots['layout'][xaxis_name]['title'] = px_fig.layout['xaxis']['title']
fig_subplots['layout'][yaxis_name]['title'] = px_fig.layout['yaxis']['title']
for px_fig, nrow in zip([fig1, fig2],[1,2]):
modify_axis_titles(fig_subplots, px_fig, nrow)
fig_subplots.show()

How to format plotly legend when using marker color?

I want to follow up on this post: Plotly: How to colorcode plotly graph objects bar chart using Python?.
When using plotly express, and specifying 'color', the legend is correctly produced as seen in the post by vestland.
This is my plotly express code:
data = {'x_data': np.random.random_sample((5,)),
'y_data': ['A', 'B', 'C', 'D', 'E'],
'c_data': np.random.randint(1, 100, size=5)
}
df = pd.DataFrame(data=data)
fig = px.bar(df,
x='x_data',
y='y_data',
orientation='h',
color='c_data',
color_continuous_scale='YlOrRd'
)
fig.show()
But when using go.Bar, the legend is incorrectly displayed as illustrated here:
This is my code using graph objects:
bar_trace = go.Bar(name='bar_trace',
x=df['x_data'],
y=df['y_data'],
marker={'color': df['c_data'], 'colorscale': 'YlOrRd'},
orientation='h'
)
layout = go.Layout(showlegend=True)
fig = go.FigureWidget(data=[bar_trace], layout=layout)
fig.show()
I'm learning how to use FigureWidget and it seems it can't use plotly express so I have to learn how to use graph objects to plot. How do I link the legend to the data such that it works like the plotly express example in vestland's post.

This really comes down to understanding what a high level API (plotly express) does. When you specify color in px if it is categorical it creates a trace per value of categorical. Hence the below two ways of creating a figure are mostly equivalent. The legend shows an item for each trace, not for each color.
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
import numpy as np
df = pd.DataFrame({"x":np.linspace(0,10,10), "y":np.linspace(5,15,10), "color":np.random.choice(list("ABCD"),10)})
px.bar(df, x="x", y="y", color="color", orientation="h").show()
fig = go.Figure()
for g in df.groupby("color"):
fig.add_trace(go.Bar(x=g[1]["x"], y=g[1]["y"], name=g[0], orientation="h"))
fig
supplementary based on comments
you do not have to use graph objects if you are using FigureWidget() as demonstrated by second figure, create with plotly express and then generate FigureWidget()
for continuous data normal pattern is to use a single trace and a colorbar (also demonstrated in second figure). However if you want a discrete legend, create a trace per value in c_data and use https://plotly.com/python-api-reference/generated/plotly.colors.html sample_colorscale()
import plotly.express as px
import plotly.colors
import plotly.graph_objects as go
import numpy as np
import pandas as pd
# simulate data frame...
df = pd.DataFrame(
{
"x_data": np.linspace(0, 10, 10),
"y_data": np.linspace(5, 15, 10),
"c_data": np.random.randint(0, 4, 10),
}
)
# build a trace per value in c_data using graph objects ... correct legend !!??
bar_traces = [
go.Bar(
name="bar_trace",
x=d["x_data"],
y=d["y_data"],
marker={
"color": plotly.colors.sample_colorscale(
"YlOrRd",
d["c_data"] / df["c_data"].max(),
)
},
orientation="h",
)
for c, d in df.groupby("c_data")
]
layout = go.Layout(showlegend=True)
fig = go.FigureWidget(data=bar_traces, layout=layout)
fig.show()
fig = px.bar(
df,
x="x_data",
y="y_data",
color="c_data",
orientation="h",
color_continuous_scale="YlOrRd",
)
fig = go.FigureWidget(data=fig.data, layout=fig.layout)
fig.show()

Plotly: How to add a horizontal line to a line graph?

I made a line graph with the code below and I'm trying to add a horizontal line at y=1. I tried following the instructions on the plotly site but it is still not showing. Does anyone know why?
date = can_tot_df.date
growth_factor = can_tot_df.growth_factor
trace0 = go.Scatter(
x=date,
y=growth_factor,
mode = 'lines',
name = 'growth_factor'
)
fig = go.Figure()
fig.add_shape(
type='line',
x0=date.min(),
y0=1,
x1=date.max(),
y1=1,
line=dict(
color='Red',
)
)
data = [trace0]
iplot(data)

Short answer, and a general solution:
fig.add_shape(type='line',
x0=0,
y0=40,
x1=8,
y1=40,
line=dict(color='Red',),
xref='x',
yref='y'
)
Details and specifics about OP's question
It's hard to tell exactly what's wrong without a sample of your data.
What I can tell for sure is that you're missing the arguments xref and yref to specify that the line is drawn as units of your y and x axis. Judging by your sample code, this is what you'd like to do since you're specifying your x-values in terms of dates.
Also, you don't need to worry about iplot for newer versions of plotly. You can display your chart just as easily by just running fig.show(). The figure and code sample below will show you how to use fig.show() and how to define your lines in terms of axis units.
Plot:
Code:
import plotly.graph_objects as go
import numpy as np
x = np.arange(10)
fig = go.Figure(data=go.Scatter(x=x, y=x**2))
fig.add_shape(type='line',
x0=0,
y0=40,
x1=8,
y1=40,
line=dict(color='Red',),
xref='x',
yref='y'
)
fig.show()
An alternative to xref='x' is xref='paper'. Now you can specify x0 as a float between 0 and 1 spanning from the start and end of the plot.

You could also use fig.add_hline(y=1) --> see https://plotly.com/python/horizontal-vertical-shapes/
import plotly.graph_objects as go
import numpy as np
x = np.arange(10)
fig = go.Figure(data=go.Scatter(x=x, y=x**2))
fig.add_hline(y=40, line_width=3, line_dash="dash", line_color="green")
fig.show()

If you use subplots, then this is the easiest way I found to add an other line to a subplot. this example draws a horizontal line at y=80 for all x values
from plotly.subplots import make_subplots
fig = make_subplots(rows=2, cols=1,
shared_xaxes=True,
vertical_spacing=0.02)
[some graph]
fig.add_trace(go.Scatter(
name='Y=80',
x = [df['date'].min(), df['date'].max()],
y = [80, 80],
mode = "lines",
marker = dict(color = 'rgba(80, 26, 80, 0.8)')
),row=1, col=1)
i found the solution on github :

df = df
fig = px.scatter(df, x="date", y="growth_factor", mode = 'lines',
hover_name=df['growth_factor'] )
fig.update_layout(shapes=[
dict(
type= 'line',
yref= 'y', y0= 1, y1= 1, # adding a horizontal line at Y = 1
xref= 'paper', x0= 0, x1= 1
)
])
fig.show()

You’re adding the line to your fig object, but fig is not getting passed into the iplot() function, only your data. So only the trace is getting plotted.
If you're using a late version of plotly, the new syntax allows you to create this plot simply using the fig object, like:
from plotly import graph_objects as go
fig = go.Figure()
# Contrived dataset for example.
x = [1, 2, 3, 4]
y = [i**2 for i in x]
fig.add_trace(go.Scatter(
x=x,
y=y,
mode = 'lines',
name = 'growth_factor'))
fig.add_shape(type='line',
x0=min(x),
y0=5,
x1=max(x),
y1=5,
line=dict(color='Red'))
fig.update_shapes(dict(xref='x', yref='y'))
fig.show()
Here are the plotly docs for convenience.