Scipy's dendrogram for agglomerative clustering requires extensive customizations to make it more informative. This package wraps scipy's dendrogram with two customizations:
- Timeseries graph at the side
- Distance labels and cluster split points
pip install dendrogram-ts
from dendrogram_ts import maxclust_draw
plt.style.use('seaborn-whitegrid')
plt.figure(figsize=(8,5));
maxclust_draw(df, 'ward', 'euclidean', max_cluster=10, ts_hspace=2)
from dendrogram_ts import colorclust_draw
import matplotlib as mpl
mpl.rcParams['lines.linewidth'] = 1
plt.style.use('seaborn-white')
plt.figure(figsize=(12,10))
colorclust_draw(df, method='ward', metric='euclidean', color_threshold=5200, ts_hspace=1)
from dendrogram_ts import allclust_draw
plt.style.use('seaborn-whitegrid')
plt.figure(figsize=(12,10))
allclust_draw(df, 'ward', 'euclidean', ts_hspace=5)