师兄师姐都在偷偷用！这个工具出手就是PNS级水准！
Matplotlib、seaborn很强，但是，参数繁多
2026可视化工具TOP3
matplotlib的强力扩展UltraPlot，它是Python matplotlib繁杂参数的简化包装，少许代码，轻松实现publication-quality plots。
network
更多。。。。。。
使用一下UltraPlot
- Chord diagram
ax.chord_diagram(matrix, ticks_interval=None, space=4)
- Ridge Plot
ax.ridgeline(data, labels=labels, overlap=0.1, cmap="managua")
- 等高线 + heatmap
ax.contourf(df, cmap="YlOrRd", colorbar="t", lw=0.7, ec="k")
- 上三角heatmap
ax.heatmap(
data,
cmap="ColdHot",
vmin=-1,
vmax=1,
N=100,
lw=0.5,
ec="k",
labels=True,
precision=2,
labels_kw={"weight": "bold"},
clip_on=False, # turn off clipping so box edges are not cut in half
)
- 流向图
fig, ax = uplt.subplots(refwidth=6.3)
ax.ribbon(
df,
id_col="country",
period_col="period",
topic_col="topic",
period_order=periods,
topic_order=topic_order,
group_map=TOPIC_TO_GROUP,
group_order=group_order,
group_colors=GROUP_COLORS,
)
nodes, edges, labels = ax.graph(
g,
layout="spring",
layout_kw={"seed": 4},
node_kw={
"node_color": degrees,
"cmap": "viko",
"edgecolors": "black",
"linewidths": 0.6,
"node_size": 128,
},
edge_kw={
"alpha": 0.4,
"width": [np.random.rand() * 4for _ in range(len(g.edges()))],
},
label_kw={"font_size": 7},
)
装一下UltraPlot
pip install ultraplot
conda install -c conda-forge ultraplot