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Description
df = pd.DataFrame(['GroupA'] * 5 + ['GroupB'] * 5, columns=['AB'])
df['CD'] = ['C'] * 3 + ['D'] * 3 + ['G'] * 4
df['EF'] = ['E'] * 6 + ['F'] * 2 + ['H'] * 2
df['F'] = np.random.normal(0, 1, 10)
df.index = ['sample' + str(i) for i in range(1, df.shape[0] + 1)]
df.head()
df_heatmap = pd.DataFrame(np.random.randn(30, 10), columns=['sample' + str(i) for i in range(1, 11)])
df_heatmap.index = ["Fea" + str(i) for i in range(1, df_heatmap.shape[0] + 1)]
df_heatmap.iloc[1, 2] = np.nan
plt.figure(figsize=(3.5, 6))
cm = pch.ClusterMapPlotter(data=df_heatmap,
col_cluster=True,row_cluster=True,
col_split=df.AB,row_split=2,
col_split_gap=0.5,row_split_gap=0.8,
label='values',row_dendrogram=True,
show_rownames=True,show_colnames=True,
row_names_side='right',
tree_kws={'row_cmap': 'Set1','colors':'blue'},verbose=0,legend_gap=5,
cmap='RdYlBu_r',xticklabels_kws={'labelrotation':-90,'labelcolor':'blue'})
plt.savefig("example0.pdf", bbox_inches='tight')
plt.show()
version: 1.7.9
python: 3.11.0
matplotlib: 3.9.2
this is what i got
