Reputation: 1
I would like to obtain a 2D Heatmap (using python) for a dataset that is already binned such that I have left and right edges for x and y and then the data I am interested (that I would like colormapped) as a function of x and y.
I give an example below of what my dataset looks like:
x_min | x_max | y_min | y_max | Data |
---|---|---|---|---|
1 | 2 | 0 | 0.1 | 10 |
2 | 3 | 0 | 0.1 | 13 |
3 | 4 | 0 | 0.1 | 12 |
4 | 5 | 0 | 0.1 | 20 |
1 | 2 | 0.1 | 0.2 | 9 |
2 | 3 | 0.1 | 0.2 | 17 |
3 | 4 | 0.1 | 0.2 | 22 |
4 | 5 | 0.1 | 0.2 | 30 |
I would like to plot a 2D Heatmap like this below: 2D Heatmap
How would that be possible so that I get a heat map that would have for Y axis from 0 to 0.2 and for X axis from 1 to 5, and a colorbar dependent on 'data'?
Thank you!
Upvotes: 0
Views: 377
Reputation: 80339
plt.imshow()
could be used as follows:
import matplotlib.pyplot as plt
import pandas as pd
from io import StringIO
data_str = '''
x_min x_max y_min y_max Data
1 2 0 0.1 10
2 3 0 0.1 13
3 4 0 0.1 12
4 5 0 0.1 20
1 2 0.1 0.2 9
2 3 0.1 0.2 17
3 4 0.1 0.2 22
4 5 0.1 0.2 30'''
df = pd.read_csv(StringIO(data_str), delim_whitespace=True)
plt.imshow(df['Data'].to_numpy().reshape(2, 4), origin='lower', extent=[1, 5, 0, 0.2], aspect='auto', cmap='plasma')
plt.colorbar()
plt.xticks(range(1, 6))
plt.yticks([0, 0.1, 0.2])
for row in df.itertuples(index=False):
plt.text((row.x_min + row.x_max) / 2, (row.y_min + row.y_max) / 2, f"{row.Data:.0f}",
color='navy' if row.Data > 22 else 'yellow', size=20, ha='center', va='center')
plt.show()
Upvotes: 1