Heat Map with DataFrame - pandas

Question

I have a pandas data frame of the form
State RF LOG KNN MLP DT LDA AB
0 AR 0.95 0.87 0.81 0.89 0.81 0.84 0.87
1 FL 0.83 0.86 0.85 0.86 0.89 0.82 0.85
2 NJ 0.89 0.81 0.88 0.83 0.89 0.84 0.83
3 NV 0.77 0.72 0.89 0.79 0.79 0.73 0.70
4 TX 0.71 0.70 0.71 0.77 0.70 0.70 0.92
5 CA 0.69 0.81 0.81 0.88 0.88 0.60 0.89
How could I make a heat map, for example, on Seaborn, that in the X-axis has the names of the columns: [RF, LOG, KNN, MLP, DT, LDA, AB], in the Y-axis the names of the column State [AR, FL, NJ, NV, TX, CA], and the corresponding values, displayed in the squares, are the "heat" indicators?

Answer 1

If you index the columns of the states, you can draw a heat map directly.
import pandas as pd
import numpy as np
import io
import seaborn as sns
sns.set_theme()
data = '''
State RF LOG KNN MLP DT LDA AB
0 AR 0.95 0.87 0.81 0.89 0.81 0.84 0.87
1 FL 0.83 0.86 0.85 0.86 0.89 0.82 0.85
2 NJ 0.89 0.81 0.88 0.83 0.89 0.84 0.83
3 NV 0.77 0.72 0.89 0.79 0.79 0.73 0.70
4 TX 0.71 0.70 0.71 0.77 0.70 0.70 0.92
5 CA 0.69 0.81 0.81 0.88 0.88 0.60 0.89
'''
df = pd.read_csv(io.StringIO(data), delim_whitespace=True)
df.set_index('State', inplace=True)
ax = sns.heatmap(df)