• This is a new feature in 5.5.0 https://github.com/plotly/plotly.py/releases. After installing and restarting my jupyter kernel, this did not work. Required restart of complete jupyter environment
• the documented example using go https://plotly.com/python/heatmaps/#text-on-heatmap-points plus note in release notes auto_text parameter, I explored this.
• below shows use of px and also go by adding numbers as text as well

import plotly.express as px
import plotly.graph_objects as go
import inflect

p = inflect.engine()
df = px.data.medals_wide(indexed=True)
fig = px.imshow(df, text_auto=True)
fig2 = go.Figure(fig.data, fig.layout)
fig2 = fig2.update_traces(text=df.applymap(p.number_to_words).values, texttemplate="%{text}", hovertemplate=None)

fig.show()
fig2.show()

dash

• see https://dash.plotly.com/external-resources Controlling the Plotly.js Version Used by dcc.Graph
• dash 2.0.0 is packaged with a version of plotly.js that does not yet support texttemplate
• code below shows how to override

import numpy as np
import dash
import plotly.graph_objects as go
import plotly.express as px
from dash.dependencies import Input, Output, State
from jupyter_dash import JupyterDash
import inflect

# Build App
app = JupyterDash(__name__, external_scripts=["https://cdn.plot.ly/plotly-2.8.3.min.js"])
app.scripts.config.serve_locally = False
app.layout = dash.html.Div(
    [
        dash.dcc.Interval(id="run", max_intervals=1),
        dash.dcc.Graph(id="fig"),
    ]
)


def hm():
    p = inflect.engine()
    df = px.data.medals_wide(indexed=True)
    fig = px.imshow(df, text_auto=True)
    fig2 = go.Figure(fig.data, fig.layout)
    fig2 = fig2.update_traces(
        text=df.applymap(p.number_to_words).values,
        texttemplate="%{text}",
        hovertemplate=None,
    )
    return fig2.update_layout(title=f"dash: {dash.__version__}")


@app.callback(Output("fig", "figure"), Input("run", "n_intervals"))
def createFig(n):
    return hm()


# Run app and display result inline in the notebook
app.run_server(mode="inline")

Well, I must admit, this is not my cleanest code, but it got the job done.

First, notice how z in data has a different order from the plotly example z. This is because yours is sorted by day, and theirs is sorted by time of day. So first I sorted using that, with a custom dictionary key, used numpy's reshape method to get it into the required shape, then converted the values to floats.

For x and y, I used list comprehensions, the list-set trick, then sorted them back to the desired order.

Last, it's just a matter of plotting.

import plotly.graph_objects as go
import numpy as np

data = [
['Monday', 'Morning', 1],
['Monday', 'Afternoon', 20],
['Monday', 'Evening', 30],
['Tuesday', 'Morning', None],
['Tuesday', 'Afternoon', 1],
['Tuesday', 'Evening', 60],
['Wednesday', 'Morning', 30],
['Wednesday', 'Afternoon', 60],
['Wednesday', 'Evening', 1],
['Thursday', 'Morning', 50],
['Thursday', 'Afternoon', 80],
['Thursday', 'Evening', -10],
['Friday', 'Morning', 1],
['Friday', 'Afternoon', 30],
['Friday', 'Evening', 20]
]


seq_time = {'Morning':0, 'Afternoon':1, 'Evening':2}
seq_day = {'Monday':0, 'Tuesday': 1, 'Wednesday':2, 'Thursday':3, 'Friday':4}
data.sort(key = lambda x: seq_time[x[1]])
z = np.array([i[2] for i in data]).reshape(3,5).astype(float)
x = sorted(list(set([i[0] for i in data])), key = lambda x: seq_day[x])
y = sorted(list(set([i[1] for i in data])), key = lambda x: seq_time[x])

fig = go.Figure(data=go.Heatmap(
                   z=z,
                   x=x,
                   y=y,
                   hoverongaps = False))
fig.show()