如何使用 Plotly 删除堆叠和分组条形图中的 x 轴刻度标签

阿隆·范比伦

我有一个数据集：

我想使用 Plotly 在堆叠和分组的条形图中可视化此数据集。不幸的是，Plotly没有这种类型的图表还没有，但这个解决办法，我尽力了。

我的代码：

sv_clusters = ["cluster_1", "cluster_2", "cluster_3", "cluster_4", "cluster_5", "cluster_6", "cluster_7"]
sv_data = sv_data[["Population", "Sample_name"] + sv_clusters]

for r in sv_clusters:
    fig.add_trace(
        go.Bar(
            x=[sv_data.Population, sv_data.Sample_name],
            y=sv_data[r],
            name=r,
            marker=dict(
                line_width=0)),
    )

fig.update_layout(
    template="simple_white",
    xaxis=dict(title_text=None),
    yaxis=dict(title_text="fraction"),
    width=2000,
    bargap=0,
    title='Alles',
    barmode="stack",

现在我的情节是这样的：

我想删除 x 标签刻度，因为它使图表混乱（样本名称而不是总体名称）。所以我尝试了showticklabels=False，结果是：

这将删除所有 x 轴标签。

如何删除样本名称刻度标签？

罗布·雷蒙德

有模拟数据使代码可重现
发现您注意到的相同问题
恢复为不使用https://plotly.com/python/categorical-axes/#multicategorical-axes但编码 xaxis
然后可以更新数组以定义刻度

import requests
import pandas as pd
import numpy as np
import plotly.graph_objects as go

# generate some data... similar to what was presented
sv_data = pd.DataFrame(
    {
        "Population": pd.json_normalize(
            requests.get("https://restcountries.eu/rest/v2/all").json()
        )["subregion"].unique()
    }
).loc[0:6,].assign(
    Sample_name=lambda d: d["Population"]
    .str[:2]
    .str.upper()
    .apply(lambda s: [f"{s}{i}" for i in range(1500, 1550)])
).explode(
    "Sample_name"
).assign(**{f"cluster_{i}":lambda d: np.random.uniform(0,1, len(d)) for i in range(1,8)})

sv_clusters = ["cluster_1", "cluster_2", "cluster_3", "cluster_4", "cluster_5", "cluster_6", "cluster_7"]
sv_data = sv_data[["Population", "Sample_name"] + sv_clusters]
fig=go.Figure()

# instead of categoricals use concatenated value for x,  define text to hover works
for r in sv_clusters:
    fig.add_trace(
        go.Bar(
            x=sv_data.loc[:,["Population","Sample_name"]].apply(lambda r: " ".join(r), axis=1),
            y=sv_data[r],
            text=sv_data.loc[:,["Population","Sample_name"]].apply(lambda r: " ".join(r), axis=1),
            name=r,
            marker=dict(
                line_width=0)),
    )

# given simple x,  set tick vals as wanted
fig.update_layout(
    template="simple_white",
    yaxis=dict(title_text="fraction"),
    width=2000,
    bargap=0,
    title='Alles',
    barmode="stack",
    xaxis={"tickmode":"array", "tickvals":sv_data.loc[:,["Population","Sample_name"]].apply(lambda r: " ".join(r), axis=1),
          "ticktext":np.where(sv_data["Population"]==sv_data["Population"].shift(), "", sv_data["Population"])}
)