How to format numbers displayed in figure factory annotated heatmap

This is going to be really noddy but can someone point me to how i format the displayed numbers in a figure factory annotated heatmap.

I have it all working the last thing is to get the floats that are currently displaying to display as ints

Here is the code, Iā€™m just running it in jupyter just now to test

# Create our temp dataframe df and pull in the data we are interested in.
# We also use this opertunity to remove blank entries
df = raca_df[['risk_id', 'gross_impact','gross_likelihood', 'business_unit', 'net_impact', 'net_likelihood']].dropna()

for item in ['gross_impact','gross_likelihood','net_impact', 'net_likelihood']:
    df[item] = df[item].astype('int')

# get our counts of the number of impact,likelihood pair
counts = df.groupby(['gross_impact','gross_likelihood']).apply(len).reset_index().values

heatmap = np.zeros((np.max(5), np.max(5)))

heatmap[counts[:,1]-1, counts[:,0]-1] = counts[:,2]

# Set up my Axis labels
x=['Minor [Very Low]<br>1', 'Important [Low]<br>2', 'Significant [Moderate]<br>3', 'Major [High]<br>4', 'Critical [Very High]<br>5']
y=['Very Remote<br>1', 'Remote<br>2', 'Unlikely<br>3', 'Possible<br>4', 'Highly Possible<br>5']

# import plotly.figure_factory as ff
fig = ff.create_annotated_heatmap(heatmap, x=x, y=y, colorscale='magma')

# Set the axes lables from the bottom. Eases readability
fig['layout']['xaxis']['side'] = 'bottom'

fig.layout.update({'title': "Gross Risk Distribution - All RACA's"}, title_x=0.5)

# display our Annotation

and if I check my dataframe info I can see the input is set to int

<class 'pandas.core.frame.DataFrame'>
Int64Index: 387 entries, 0 to 1157
Data columns (total 6 columns):
 #   Column            Non-Null Count  Dtype   
---  ------            --------------  -----   
 0   risk_id           387 non-null    category
 1   gross_impact      387 non-null    int32   
 2   gross_likelihood  387 non-null    int32   
 3   business_unit     387 non-null    category
 4   net_impact        387 non-null    int32   
 5   net_likelihood    387 non-null    int32   
dtypes: category(2), int32(4)
memory usage: 22.5 KB

Thanks for your help

1 Like

Figured it out.

my numpy Array defaults to float. I changed its dtype to int and now all is good

heatmap = np.zeros((np.max(5), np.max(5)),dtype=int)

This is still an important question for those of us who want to set the number of decimal points for a floating point number. Iā€™m getting hugely long floats displayed.

I found an answer to this here: