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Python Plotly display other information on Hover

Here is the code that I have tried:
# import pandas as pd
import numpy as np
import plotly.graph_objects as go
from plotly.subplots import make_subplots
df = pd.read_csv("resultant_data.txt", index_col = 0, sep = ",")
display=df[["Velocity", "WinLoss"]]
pos = lambda col : col[col > 0].sum()
neg = lambda col : col[col < 0].sum()
Related_Display_Info = df.groupby("RacerCount").agg(Counts=("Velocity","count"),
WinLoss=("WinLoss","sum"),
Positives=("WinLoss", pos),
Negatives=("WinLoss", neg),
)
# Create figure with secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])
# Add traces
fig.add_trace(
go.Scatter(x=display.index, y=display["Velocity"], name="Velocity", mode="markers"),
secondary_y=False
)
fig.add_trace(
go.Scatter(x=Related_Display_Info.index,
y=Related_Display_Info["WinLoss"],
name="Win/Loss",
mode="markers",
marker=dict(
color=(
(Related_Display_Info["WinLoss"] < 0)
).astype('int'),
colorscale=[[0, 'green'], [1, 'red']]
)
),
secondary_y=True,
)
# Add figure title
fig.update_layout(
title_text="Race Analysis"
)
# Set x-axis title
fig.update_xaxes(title_text="<b>Racer Counts</b>")
# Set y-axes titles
fig.update_yaxes(title_text="<b>Velocity</b>", secondary_y=False)
fig.update_yaxes(title_text="<b>Win/Loss/b>", secondary_y=True)
fig.update_layout(hovermode="x unified")
fig.show()
The output is:
But I was willing to display the following information when I hover on the point:
RaceCount = From Display dataframe value Number of the race corresponding to the dot I hover on.
Velocity = From Display Dataframe value Velocity at that point
Counts = From Related_Display_Info Column
WinLoss = From Related_Display_Info Column
Positives = From Related_Display_Info Column
Negatives = From Related_Display_Info Column
Please can anyone tell me what to do to get this information on my chart?
I have checked this but was not helpful since I got many errors: Python/Plotly: How to customize hover-template on with what information to show?
Data:
RacerCount,Velocity,WinLoss
111,0.36,1
141,0.31,1
156,0.3,1
141,0.23,1
147,0.23,1
156,0.22,1
165,0.2,1
174,0.18,1
177,0.18,1
183,0.18,1
114,0.32,1
117,0.3,1
120,0.29,1
123,0.29,1
126,0.28,1
129,0.27,1
120,0.32,1
144,0.3,1
147,0.3,1
159,0.27,1
165,0.26,1
168,0.25,1
156,0.29,1
165,0.26,1
168,0.26,1
165,0.28,1
213,0.17,1
243,0.15,1
249,0.14,1
228,0.54,1
177,0.67,1
180,0.66,1
183,0.65,1
192,0.66,1
195,0.62,1
198,0.6,1
180,0.66,1
222,0.56,1
114,0.41,1
81,0.82,1
102,0.56,1
111,0.55,1
90,1.02,1
93,1.0,1
90,1.18,1
90,1.18,1
93,1.1,1
96,1.07,1
99,1.04,1
102,0.99,1
105,0.94,1
108,0.92,1
111,0.9,1
162,0.66,1
159,0.63,1
162,0.65,-1
162,0.66,-1
168,0.64,-1
159,0.68,-1
162,0.67,-1
174,0.62,-1
168,0.65,-1
171,0.64,-1
198,0.55,-1
300,0.47,-1
201,0.56,-1
174,0.63,-1
180,0.61,-1
171,0.64,-1
174,0.62,-1
303,0.47,-1
312,0.48,-1
258,0.51,-1
261,0.51,-1
264,0.5,-1
279,0.47,-1
288,0.48,-1
294,0.47,-1
258,0.52,-1
261,0.51,-1
267,0.5,-1
222,0.53,-1
171,0.64,-1
177,0.63,-1
177,0.63,-1

Essentially, this code ungroups the data frame before plotting to create the hovertemplate you're looking for.
As stated in the comments, the data has to have the same number of rows to be shown in the hovertemplate. At the end of my answer, I added the code all in one chunk.
Since you have hovermode as x unified, you probably only want one of these traces to have hover content.
I slightly modified the creation of Related_Display_Info. Instead of WinLoss, which is already in the parent data frame, I modified it to WinLoss_sum, so there wouldn't be a naming conflict when I ungrouped.
Related_Display_Info = df.groupby("RacerCount").agg(
Counts=("Velocity","count"), WinLoss_sum=("WinLoss","sum"),
Positives=("WinLoss", pos), Negatives=("WinLoss", neg))
Now it's time to ungroup the data you grouped. I created dui (stands for display info ungrouped).
dui = pd.merge(df, Related_Display_Info, how = "outer", on="RacerCount",
suffixes=(False, False))
I created the hovertemplate for both traces. I passed the entire ungrouped data frame to customdata. It looks like the only column that isn't in the template is the original WinLoss.
# create hover template for all traces
ht="<br>".join(["<br>RacerCount: %{customdata[0]}",
"Velocity: %{customdata[1]:.2f}",
"Counts: %{customdata[3]}",
"Winloss: %{customdata[4]}",
"Positives: %{customdata[5]}",
"Negatives: %{customdata[6]}<br>"])
The creation of fig is unchanged. However, the traces are both based on dui. Additionally, the index isn't RacerCount, so I used the literal field instead.
# Create figure with secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])
# Add traces
fig.add_trace(go.Scatter(x=dui["RacerCount"], y=dui["Velocity"],
name="Velocity", mode="markers",
customdata=dui, hovertemplate=ht),
secondary_y=False)
fig.add_trace(
go.Scatter(x = dui["RacerCount"], y=dui["WinLoss_sum"], customdata=dui,
name="Win/Loss", mode="markers",
marker=dict(color=((dui["WinLoss_sum"] < 0)).astype('int'),
colorscale=[[0, 'green'], [1, 'red']]),
hovertemplate=ht),
secondary_y=True)
All the code altogether (for easier copy + paste)
import pandas as pd
import numpy as np
import plotly.graph_objects as go
from plotly.subplots import make_subplots
df = pd.read_clipboard(sep = ',')
display=df[["Velocity", "WinLoss"]]
pos = lambda col : col[col > 0].sum()
neg = lambda col : col[col < 0].sum()
Related_Display_Info = df.groupby("RacerCount").agg(
Counts=("Velocity","count"), WinLoss_sum=("WinLoss","sum"),
Positives=("WinLoss", pos), Negatives=("WinLoss", neg))
# ungroup the data for the hovertemplate
dui = pd.merge(df, Related_Display_Info, how = "outer", on="RacerCount",
suffixes=(False, False))
# create hover template for all traces
ht="<br>".join(["<br>RacerCount: %{customdata[0]}",
"Velocity: %{customdata[1]:.2f}",
"Counts: %{customdata[3]}",
"Winloss: %{customdata[4]}",
"Positives: %{customdata[5]}",
"Negatives: %{customdata[6]}<br>"])
# Create figure with secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])
# Add traces
fig.add_trace(go.Scatter(x=dui["RacerCount"], y=dui["Velocity"],
name="Velocity", mode="markers",
customdata=dui, hovertemplate=ht),
secondary_y=False)
fig.add_trace(
go.Scatter(x = dui["RacerCount"], y=dui["WinLoss_sum"], customdata=dui,
name="Win/Loss", mode="markers",
marker=dict(color=((dui["WinLoss_sum"] < 0)).astype('int'),
colorscale=[[0, 'green'], [1, 'red']]),
hovertemplate=ht),
secondary_y=True)
# Add figure title
fig.update_layout(
title_text="Race Analysis"
)
# Set x-axis title
fig.update_xaxes(title_text="<b>Racer Counts</b>")
# Set y-axes titles
fig.update_yaxes(title_text="<b>Velocity</b>", secondary_y=False)
fig.update_yaxes(title_text="<b>Win/Loss/b>", secondary_y=True)
fig.update_layout(hovermode="x unified")
fig.show()

Connecting data points with lines in a Plotly boxplot in Python

I am working on some boxplots. I found this code very helpful and I managed to replicate it for my needs:
import plotly.express as px
import numpy as np
import pandas as pd
np.random.seed(1)
y0 = np.random.randn(50) - 1
y1 = np.random.randn(50) + 1
df = pd.DataFrame({'graph_name':['trace 0']*len(y0)+['trace 1']*len(y1),
'value': np.concatenate([y0,y1],0),
'color':np.random.choice([0,1,2,3,4,5,6,7,8,9], size=100, replace=True)}
)
fig = px.strip(df,
x='graph_name',
y='value',
color='color',
stripmode='overlay')
fig.add_trace(go.Box(y=df.query('graph_name == "trace 0"')['value'], name='trace 0'))
fig.add_trace(go.Box(y=df.query('graph_name == "trace 1"')['value'], name='trace 1'))
fig.update_layout(autosize=False,
width=600,
height=600,
legend={'traceorder':'normal'})
fig.show()
I am now trying to put some lines connecting the datapoints with the same colors, but I am lost. Any idea?
Something similar to this:

My first idea was to add lines to your figure by using plotly shapes and specifying the start and end points in x- and y-axis coordinates. However, when you use px.strip, plotly implements jittering (adding randomly generated small values, say between -0.1 and 0.1, to the x-coordinates under the hood to avoid points overlapping), but as far as I know, there is no way to retrieve the exact x-coordinates of each point.
However we can get around this by using go.Scatter to plot all the paired points individually, adding jittering as needed to the x-values and connecting each pair of points with a line. We are basically implementing px.strip ourselves but with full control of the exact coordinates of each point.
In order to toggle colors the same way that px.strip allows you to, we need to assign all points of the same color to the same legendgroup, and also only show the legend entry the first time a color is plotted (as we don't want an legend entry for each point)
import plotly.express as px
import plotly.graph_objects as go
import numpy as np
import pandas as pd
np.random.seed(1)
y0 = np.random.randn(50) - 1
y1 = np.random.randn(50) + 1
## sort both sets of data so we can easily connect them with line annotations
y0.sort()
y1.sort()
df = pd.DataFrame({'graph_name':['trace 0']*len(y0)+['trace 1']*len(y1),
'value': np.concatenate([y0,y1],0)}
# 'color':np.random.choice([0,1,2,3,4,5,6,7,8,9], size=100, replace=True)}
)
fig = go.Figure()
## i will set jittering to 0.1
x0 = np.array([0]*len(y0)) + np.random.uniform(-0.1,0.1,len(y0))
x1 = np.array([1]*len(y0)) + np.random.uniform(-0.1,0.1,len(y0))
## px.colors.sequential.Plasma contains 10 distinct colors
## colors_list = np.random.choice(px.colors.qualitative.D3, size=50)
## for simplicity, we repeat it 5 times instead of selecting randomly
## this guarantees the colors appear in order in the legend
colors_list = px.colors.qualitative.D3*5
color_number = {i:color for color,i in enumerate(px.colors.qualitative.D3)}
## keep track of whether the color is showing up for the first time as we build out the legend
colors_legend = {color:False for color in colors_list}
for x_start,x_end,y_start,y_end,color in zip(x0,x1,y0,y1,colors_list):
## if the color hasn't been added to the legend yet, add a legend entry
if colors_legend[color] == False:
fig.add_trace(
go.Scatter(
x=[x_start,x_end],
y=[y_start,y_end],
mode='lines+markers',
marker=dict(color=color),
line=dict(color="rgba(100,100,100,0.5)"),
legendgroup=color_number[color],
name=color_number[color],
showlegend=True,
hoverinfo='skip'
)
)
colors_legend[color] = True
## otherwise omit the legend entry, but add it to the same legend group
else:
fig.add_trace(
go.Scatter(
x=[x_start,x_end],
y=[y_start,y_end],
mode='lines+markers',
marker=dict(color=color),
line=dict(color="rgba(100,100,100,0.5)"),
legendgroup=color_number[color],
showlegend=False,
hoverinfo='skip'
)
)
fig.add_trace(go.Box(y=df.query('graph_name == "trace 0"')['value'], name='trace 0'))
fig.add_trace(go.Box(y=df.query('graph_name == "trace 1"')['value'], name='trace 1'))
fig.update_layout(autosize=False,
width=600,
height=600,
legend={'traceorder':'normal'})
fig.show()

How to get bar colors of multiple traces from bar chart?

I created a bar chart with multiple traces using a loop. The colors of each trace are assigned by plotly automatically. Now chart is done, how to get colors of all traces? I needed to assign these same colors to another scatter plot inside subplots to make color consistent. Thank you so much for your help.
for i in range (10):
fig.add_trace(
go.Bar(
x=weights_df_best.index,
y=weights_df_best[col].values,
name = col,
text=col,
hoverinfo='text',
legendgroup = '1',
offsetgroup=0,
),
row=1,
col=1,
)

If you'd like to put the colors in a list after you've produced a figure, just run:
colors = []
fig.for_each_trace(lambda t: colors.append(t.marker.color))
If you use that approach in the complete snippet below, you'll get
['#636efa', '#EF553B', '#00cc96']
Plot
Complete code:
import plotly.express as px
df = px.data.medals_long()
fig = px.bar(df, x="medal", y="count", color="nation", text_auto=True)
colors = []
fig.for_each_trace(lambda t: colors.append(t.marker.color))
colors

How to color lines on mouseover in a bump chart using Altair Viz?

The goal is to highlight the entire line when hovering anywhere (not just at the data points) on the line.
Imports:
from IPython.display import display
import pandas as pd
import altair as alt
Data:
data = '{"Date":{"5":1560643200000,"18":1560643200000,"22":1560643200000,"24":1560643200000,"59":1560643200000,"65":1561248000000,"78":1561248000000,"82":1561248000000,"84":1561248000000,"119":1561248000000,"125":1561852800000,"138":1561852800000,"142":1561852800000,"144":1561852800000,"179":1561852800000,"185":1562457600000,"198":1562457600000,"202":1562457600000,"204":1562457600000,"239":1562457600000,"245":1563062400000,"258":1563062400000,"262":1563062400000,"264":1563062400000,"299":1563062400000,"305":1563667200000,"318":1563667200000,"322":1563667200000,"324":1563667200000,"359":1563667200000,"365":1564272000000,"378":1564272000000,"382":1564272000000,"384":1564272000000,"419":1564272000000,"425":1564876800000,"438":1564876800000,"442":1564876800000,"444":1564876800000,"479":1564876800000,"485":1565481600000,"498":1565481600000,"502":1565481600000,"504":1565481600000,"539":1565481600000,"545":1566086400000,"558":1566086400000,"562":1566086400000,"564":1566086400000,"599":1566086400000,"605":1566691200000,"618":1566691200000,"622":1566691200000,"624":1566691200000,"659":1566691200000,"665":1567296000000,"678":1567296000000,"682":1567296000000,"684":1567296000000,"719":1567296000000,"725":1567900800000,"738":1567900800000,"742":1567900800000,"744":1567900800000,"779":1567900800000,"785":1568505600000,"798":1568505600000,"802":1568505600000,"804":1568505600000,"839":1568505600000,"845":1569110400000,"858":1569110400000,"862":1569110400000,"864":1569110400000,"899":1569110400000,"905":1569715200000,"918":1569715200000,"922":1569715200000,"924":1569715200000,"959":1569715200000,"965":1570320000000,"978":1570320000000,"982":1570320000000,"984":1570320000000,"1019":1570320000000,"1025":1570924800000,"1038":1570924800000,"1042":1570924800000,"1044":1570924800000,"1079":1570924800000,"1085":1571529600000,"1098":1571529600000,"1102":1571529600000,"1104":1571529600000,"1139":1571529600000,"1145":1572134400000,"1158":1572134400000,"1162":1572134400000,"1164":1572134400000,"1199":1572134400000,"1205":1572739200000,"1218":1572739200000,"1222":1572739200000,"1224":1572739200000,"1259":1572739200000,"1265":1573344000000,"1278":1573344000000,"1282":1573344000000,"1284":1573344000000,"1319":1573344000000,"1325":1573948800000,"1338":1573948800000,"1342":1573948800000,"1344":1573948800000,"1379":1573948800000,"1385":1574553600000,"1398":1574553600000,"1402":1574553600000,"1404":1574553600000,"1439":1574553600000,"1445":1575158400000,"1458":1575158400000,"1462":1575158400000,"1464":1575158400000,"1499":1575158400000,"1505":1575763200000,"1518":1575763200000,"1522":1575763200000,"1524":1575763200000,"1559":1575763200000,"1565":1576368000000,"1578":1576368000000,"1582":1576368000000,"1584":1576368000000,"1619":1576368000000},"Store":{"5":"store1","18":"store2","22":"store3","24":"store4","59":"store5","65":"store1","78":"store2","82":"store3","84":"store4","119":"store5","125":"store1","138":"store2","142":"store3","144":"store4","179":"store5","185":"store1","198":"store2","202":"store3","204":"store4","239":"store5","245":"store1","258":"store2","262":"store3","264":"store4","299":"store5","305":"store1","318":"store2","322":"store3","324":"store4","359":"store5","365":"store1","378":"store2","382":"store3","384":"store4","419":"store5","425":"store1","438":"store2","442":"store3","444":"store4","479":"store5","485":"store1","498":"store2","502":"store3","504":"store4","539":"store5","545":"store1","558":"store2","562":"store3","564":"store4","599":"store5","605":"store1","618":"store2","622":"store3","624":"store4","659":"store5","665":"store1","678":"store2","682":"store3","684":"store4","719":"store5","725":"store1","738":"store2","742":"store3","744":"store4","779":"store5","785":"store1","798":"store2","802":"store3","804":"store4","839":"store5","845":"store1","858":"store2","862":"store3","864":"store4","899":"store5","905":"store1","918":"store2","922":"store3","924":"store4","959":"store5","965":"store1","978":"store2","982":"store3","984":"store4","1019":"store5","1025":"store1","1038":"store2","1042":"store3","1044":"store4","1079":"store5","1085":"store1","1098":"store2","1102":"store3","1104":"store4","1139":"store5","1145":"store1","1158":"store2","1162":"store3","1164":"store4","1199":"store5","1205":"store1","1218":"store2","1222":"store3","1224":"store4","1259":"store5","1265":"store1","1278":"store2","1282":"store3","1284":"store4","1319":"store5","1325":"store1","1338":"store2","1342":"store3","1344":"store4","1379":"store5","1385":"store1","1398":"store2","1402":"store3","1404":"store4","1439":"store5","1445":"store1","1458":"store2","1462":"store3","1464":"store4","1499":"store5","1505":"store1","1518":"store2","1522":"store3","1524":"store4","1559":"store5","1565":"store1","1578":"store2","1582":"store3","1584":"store4","1619":"store5"},"Rank":{"5":1.0,"18":1.0,"22":1.0,"24":1.0,"59":1.0,"65":2.0,"78":2.0,"82":2.0,"84":2.0,"119":2.0,"125":2.0,"138":2.0,"142":2.0,"144":2.0,"179":2.0,"185":2.0,"198":2.0,"202":2.0,"204":2.0,"239":2.0,"245":2.0,"258":2.0,"262":2.0,"264":2.0,"299":2.0,"305":2.0,"318":2.0,"322":2.0,"324":2.0,"359":2.0,"365":2.0,"378":2.0,"382":2.0,"384":1.0,"419":2.0,"425":3.0,"438":1.0,"442":3.0,"444":2.0,"479":3.0,"485":4.0,"498":1.0,"502":4.0,"504":3.0,"539":4.0,"545":4.0,"558":1.0,"562":3.0,"564":3.0,"599":4.0,"605":5.0,"618":1.0,"622":2.0,"624":4.0,"659":5.0,"665":6.0,"678":1.0,"682":2.0,"684":5.0,"719":6.0,"725":7.0,"738":1.0,"742":2.0,"744":5.0,"779":7.0,"785":8.0,"798":1.0,"802":2.0,"804":6.0,"839":8.0,"845":8.0,"858":1.0,"862":2.0,"864":5.0,"899":8.0,"905":8.0,"918":1.0,"922":2.0,"924":4.0,"959":8.0,"965":8.0,"978":1.0,"982":2.0,"984":4.0,"1019":8.0,"1025":10.0,"1038":1.0,"1042":2.0,"1044":5.0,"1079":10.0,"1085":10.0,"1098":1.0,"1102":2.0,"1104":5.0,"1139":10.0,"1145":11.0,"1158":1.0,"1162":2.0,"1164":5.0,"1199":11.0,"1205":12.0,"1218":1.0,"1222":2.0,"1224":6.0,"1259":12.0,"1265":13.0,"1278":2.0,"1282":1.0,"1284":7.0,"1319":13.0,"1325":13.0,"1338":2.0,"1342":1.0,"1344":6.0,"1379":13.0,"1385":14.0,"1398":2.0,"1402":1.0,"1404":6.0,"1439":14.0,"1445":3.0,"1458":2.0,"1462":1.0,"1464":6.0,"1499":8.0,"1505":3.0,"1518":2.0,"1522":1.0,"1524":6.0,"1559":4.0,"1565":3.0,"1578":2.0,"1582":1.0,"1584":8.0,"1619":5.0}}'
Dataframe:
df_slim = pd.read_json(data)
Chart:
highlight = alt.selection(type='single', on='mouseover',
fields=['Store'], nearest=True, empty="none")
chart = alt.Chart(df_slim).mark_line().encode(
x='Date',
y='Rank',
#color='Store',
strokeDash='Store',
color=alt.condition(highlight, 'Store', alt.value("lightgray")),
tooltip=['Rank','Store']
).properties(
width=800,
height=600,
title='Bump Chart: Store Ranking'
).configure_title(
fontSize=30,
font='Courier',
anchor='start',
color='gray'
).add_selection(
highlight
)
display(chart)
Output:
Any help? Not sure what went wrong here.

Good question! It turns out this is one of the current limitations of Vega-Lite. I found this note in the VL docs on Nearest Value
The nearest transform is not supported for continuous mark types (i.e., line and area). For these mark types, consider layering a discrete mark type (e.g., point) with a 0-value opacity
So for your example I would do something like this
highlight = alt.selection(type='single', on='mouseover',
fields=['Store'], nearest=True, empty="none")
chart = alt.Chart(df_slim).mark_line().encode(
x='Date',
y='Rank',
#color='Store',
strokeDash='Store',
color=alt.condition(highlight, 'Store', alt.value("lightgray")),
tooltip=['Rank','Store']
)
points = alt.Chart(df_slim).mark_point(opacity=0).encode(
x='Date',
y='Rank',).add_selection(
highlight
)
chart + points

Hoverinformation for shapes in plotly

I know there is the hovertemplate/hover_text/ option for traces (marker/line) but I cannot find such a thing for shapes.
Is there a way to have a hover text pop up when moving over a shape? Maybe a workaround?
Example:
import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Scatter(
x=[1.5, 3],
y=[2.5, 2.5],
text=["Rectangle reference to the plot",
"Rectangle reference to the axes"],
mode="markers",
))
fig.add_shape(
# Rectangle reference to the plot
type="rect",
xref="paper",
yref="paper",
x0=0.25,
y0=0,
x1=0.5,
y1=0.5,
line=dict(
color="LightSeaGreen",
width=3,
),
fillcolor="PaleTurquoise",
)
When I hover over the two points, I get a hover-template with information. How can I get something similar for the shape?

It seems that it's not possible to add hoverinfo to shapes directly. But you can obtain something very close to what seems to be the desired effect through the right combination of shapes and traces. The following plot is made from specifying two rectangles in a list like:
shapes = [[2,6,2,6],
[4,7,4,7]]
The rest of the code snippet is set up to be flexible with regards to the number of shapes, and the colors assigned to them and the corresponding traces to make that little dot in the lower right corners of the shapes.
Plot:
If this is something you can use, we can discuss ways to edit what is being displayed in the hoverinfo.
Complete code:
# Imports
import pandas as pd
#import matplotlib.pyplot as plt
import numpy as np
import plotly.graph_objects as go
import plotly.express as px
# shape definitions
shapes = [[2,6,2,6],
[4,7,4,7]]
# color management
# define colors as a list
colors = px.colors.qualitative.Plotly
# convert plotly hex colors to rgba to enable transparency adjustments
def hex_rgba(hex, transparency):
col_hex = hex.lstrip('#')
col_rgb = list(int(col_hex[i:i+2], 16) for i in (0, 2, 4))
col_rgb.extend([transparency])
areacol = tuple(col_rgb)
return areacol
rgba = [hex_rgba(c, transparency=0.4) for c in colors]
colCycle = ['rgba'+str(elem) for elem in rgba]
# plotly setup
fig = go.Figure()
# shapes
for i, s in enumerate(shapes):
fig.add_shape(dict(type="rect",
x0=s[0],
y0=s[2],
x1=s[1],
y1=s[3],
layer='above',
fillcolor=colCycle[i],
line=dict(
color=colors[i],
width=3)))
# traces as dots in the lower right corner for each shape
for i, s in enumerate(shapes):
fig.add_trace(go.Scatter(x=[s[1]], y=[s[2]], name = "Hoverinfo " +str(i + 1),
showlegend=False,
mode='markers', marker=dict(color = colors[i], size=12)))
# edit layout
fig.update_layout(yaxis=dict(range=[0,8], showgrid=True),
xaxis=dict(range=[0,8], showgrid=True))
fig.show()

I thought of a solution I am happy with.
Simply draw a shape. You won't be able to see a hover text. However, if you add a trace with a fill on top of the shape, then set the trace to opacity=0 you will see the hover text from the trace pop up when moving over the shape.
Again, thanks for your responses!
import plotly.graph_objects as go
# Draw shape (you won't be able to add a hover text for it)
fig = go.Figure()
fig.add_shape(
type="rect",
x0=0, y0=0,
x1=4, y1=3,
fillcolor='LightSkyBlue',
line_color='Blue',
name='Shape 1'
)
# Adding a trace with a fill, setting opacity to 0
fig.add_trace(
go.Scatter(
x=[0,0,4,4,0],
y=[0,3,3,0,0],
fill="toself",
mode='lines',
name='',
text='Custom text on top of shape',
opacity=0
)
)
fig.show()