# Disappearing Data when adding annotations - Plotly
**URL:** https://community.plotly.com/t/disappearing-data-when-adding-annotations-plotly/84205
**Category:** đź“Š Plotly Python
**Created:** [May 2, 2024, 1:51pm UTC](https://community.plotly.com/t/disappearing-data-when-adding-annotations-plotly/84205 "2024-05-02T13:51:20Z")
**Posts on this page:** 3
**Page:** 1
### Author:  [@mattgifs](https://community.plotly.com/u/mattgifs)
#### Post date: [May 2, 2024, 1:51pm UTC](https://community.plotly.com/t/disappearing-data-when-adding-annotations-plotly/84205/1 "2024-05-02T13:51:20Z")
I have a facetted bar plot using both facet\_row and facet\_col. I need to have annotations for the value of facet\_row on each of the individual facets created.
I have tried using xref=paper, which results in all the annotations being more than slightly askew. This is also complicated by the fact that depending on the selected dataset, the number of facet\_cols can change, which seems to further change the position of the annotations I apply.
I have tried looping through facet\_col and facet\_row values and applying annotations based on xref=xn domain, which just results in an error that I haven’t been able to find a solution for. This would be the preferred method too, because I want the labels ON the resulting facets themselves.
I have tried an additional method where I am able to get the annotations on the facets themselves with reasonably stable position, but then all the data disappears from the plots. Shown below.
```auto
import pandas as pd
import numpy as np
import plotly.express as px
# Define the date range and number of days
start_date = '2023-01-01'
end_date = '2023-01-31'
dates = pd.date_range(start=start_date, end=end_date)
# Define the metric names and markets
metric_names = ['Metric1', 'Metric2', 'Metric3', 'Metric4', 'Metric5']
markets = ['Market1', 'Market2', 'Market3', 'Market4', 'Market5']
# Create a product of dates, metric names, and markets
date_metric_market_triples = [(date, metric, market) for date in dates for metric in metric_names for market in markets]
# Create the DataFrame
df = pd.DataFrame(date_metric_market_triples, columns=['Date', 'Metric_Name', 'Market'])
# Add random metric values
df['Metric_Value'] = np.random.randint(0, 100, size=len(df))
# Group and reset the index to make plotting easier
grouped_data = df.groupby(['Date', 'Metric_Name', 'Market']).sum().reset_index()
# Creating the bar plot with Plotly Express
fig = px.bar(grouped_data, x='Date', y='Metric_Value',
facet_col='Market', facet_row='Metric_Name',
category_orders={"Metric_Name": ['Metric1', 'Metric2', 'Metric3', 'Metric4', 'Metric5'],
"Market": ['Market1', 'Market2', 'Market3', 'Market4', 'Market5']},
title='Sum of Metric Values by Date, Metric, and Market')
# Adjust layout for better visibility
fig.update_layout(
height=1200, # Increase figure height for better visibility
width=1600 # Increase figure width to accommodate more facets
)
# Adding annotations for MetricName in each facet without overwriting plot data
for i, metric_name in enumerate(metric_names):
for j, market in enumerate(markets):
fig.add_annotation(
dict(
x=0.5, # Position of the annotation at the middle of the x-axis
y=1.05, # Position slightly above the top of the y-axis within each subplot
text=metric_name, # Text to display (Metric Name)
xref=f"x{len(markets) * i + j + 1}", # Correct axis reference for x-axis
yref=f"y{len(markets) * i + j + 1}", # Correct axis reference for y-axis
showarrow=False,
font=dict(size=10, color="black"),
xanchor='center', # Center align text
yanchor='bottom' # Bottom align text relative to the specified y coordinate
)
)
# Show the figure
fig.show()
```
Can someone please provide some assistance?
Thanks,
Matt
---
### Author:  [@davidharris](https://community.plotly.com/u/davidharris)
#### Post date: [May 3, 2024, 7:05am UTC](https://community.plotly.com/t/disappearing-data-when-adding-annotations-plotly/84205/3 "2024-05-03T07:05:44Z")
If you use _xref=f"x{index} domain"_ rather than _xref=f"x{index}"_, the thing is that you have to specify _“x domain”_ when you want _“x1 domain”_. (Ditto for y)
So if you change your annotation loop to this, it produces results that I think are close to what you are looking for:
```python
# Adding annotations for MetricName in each facet without overwriting plot data
for i, metric_name in enumerate(metric_names):
for j, market in enumerate(markets):
index = len(markets) * i + j + 1
fig.add_annotation(
dict(
x=0.5, # Position of the annotation at the middle of the x-axis
y=1.05, # Position slightly above the top of the y-axis within each subplot
text=metric_name, # Text to display (Metric Name)
xref=f"x{index} domain" if index > 1 else "x domain", # Correct axis reference for x-axis
yref=f"y{index} domain" if index > 1 else "y domain", # Correct axis reference for y-axis
showarrow=False,
font=dict(size=10, color="black"),
xanchor='center', # Center align text
yanchor='bottom' # Bottom align text relative to the specified y coordinate
)
)
```
---
### Author:  [@mattgifs](https://community.plotly.com/u/mattgifs)
#### Post date: [May 3, 2024, 2:27pm UTC](https://community.plotly.com/t/disappearing-data-when-adding-annotations-plotly/84205/4 "2024-05-03T14:27:04Z")
> [@davidharris](#):
>
> ```auto
> # Adding annotations for MetricName in each facet without overwriting plot data
> for i, metric_name in enumerate(metric_names):
> for j, market in enumerate(markets):
> index = len(markets) * i + j + 1
> fig.add_annotation(
> dict(
> x=0.5, # Position of the annotation at the middle of the x-axis
> y=1.05, # Position slightly above the top of the y-axis within each subplot
> text=metric_name, # Text to display (Metric Name)
> xref=f"x{index} domain" if index > 1 else "x domain", # Correct axis reference for x-axis
> yref=f"y{index} domain" if index > 1 else "y domain", # Correct axis reference for y-axis
> showarrow=False,
> font=dict(size=10, color="black"),
> xanchor='center', # Center align text
> yanchor='bottom' # Bottom align text relative to the specified y coordinate
> )
> )
>
> ```
Sure enough, that seems to have done the trick. Thanks David!