CODEWITHSUNDEEP
pythonplotly
user1trill
user1trill

Reputation: 105

Fixed heatmap table with customised colours

I've been breaking my head with this problem. I want to make in plotly something like this: enter image description here

This is very common in excel plots, so I want to see if it is possible to make this in Plotly for python.

The idea is to customise the plot, I mean, show exactly what the image above shows, I need this to use it as a background in another plot that I made. So, I need to know if its possible to make something like this:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors
Index= ['1', '2', '3', '4', '5']
Cols = ['A', 'B', 'C', 'D','E']
data= [[ 0, 0,1, 1,2],[ 0, 1,2, 2,3],[ 1, 2,2, 3,4],[1, 2,3, 4,4],[ 2, 3,4, 4,4]]
df = pd.DataFrame(data, index=Index, columns=Cols)
cmap = colors.ListedColormap(['darkgreen','lightgreen','yellow','orange','red'])
bounds=[0, 1, 2, 3, 4,5]
norm = colors.BoundaryNorm(bounds, cmap.N)
heatmap = plt.pcolor(np.array(data), cmap=cmap, norm=norm)
plt.colorbar(heatmap, ticks=[0, 1, 2, 3,4,5])
plt.show()

And that code give us this plot: enter image description here

Sorry to bother but by this point I'm completely hopeless haha, I've searched a lot and found nothing.

Thanks so much for reading, any help is appreciated.

Upvotes: 0

Views: 137

Answers (2)

r-beginners
r-beginners

Reputation: 35135

The MPL heatmap you presented has some remaining issues but was created plotly. I used this example from the official reference as a basis.

import plotly.express as px

data= [[ 0, 0, 1, 1, 2],[ 0, 1, 2, 2, 3],[ 1, 2, 2, 3, 4],[1, 2, 3, 4, 4],[2, 3, 4, 4, 4]]

fig = px.imshow(data, color_continuous_scale=["darkgreen","lightgreen","yellow","orange","red"])

fig.update_yaxes(autorange=True)
fig.update_layout(
    xaxis = dict(
        tickmode = 'linear',
        tick0 = 0,
        dtick = 1
    ),
    autosize=False,
    width=500
)
# fig.layout['coloraxis']['colorbar']['x'] = 1.0
fig.update_layout(coloraxis_colorbar=dict(
    tickvals=[0,1,2,3,4],
    ticktext=[0,1,2,3,4],
    x=1.0
))

fig.show()

enter image description here

Upvotes: 1

Hue
Hue

Reputation: 59

I would recommend using Seaborn colour pattern: https://seaborn.pydata.org/tutorial/color_palettes.html And playing around with the cmap, max, vmin and central which allow you to change the tone of colors base on the scale of data. (It may take a while to get what you want :D)

g = sns.heatmap(data, vmax = 6, vmin = 0, cmap = 'Spectral', center = 3, yticklabels = True)

Upvotes: 1

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