如何在 Python Plotly 中显示时间戳 x 轴 [英] How to show timestamp x-axis in Python Plotly

问题描述

我想绘制

但是，x-index 显示数字.相反，我希望在 x 轴上有一个时间戳(月+年).

编辑添加流动的

fig.update_layout(yaxis=dict(title=''),xaxis=dict(标题='时间戳'，tickformat = '%Y-%b',))

给

这似乎不是从数据索引中读取 x 轴.

解决方案

如果你想使用 bar，在我看来你需要找到一个好的解决方法.你有没有考虑过使用Heatmap?

将熊猫导入为 pd导入 plotly.graph_objsdf = pd.read_csv("availability3.txt",parse_dates=["时间戳"]).drop("未命名:0", axis=1)# 你想让变量作为列df = pd.pivot_table(df,index="时间戳",列=变量"，值=值")fig = go.Figure()fig.add_trace(去.热图(z=df.values.T,x=df.index,y=df.columns,colorscale='RdYlGn',xgap=1,ygap=2))图.show()

I want to plot this data to evaluate data availability. I used the following plotting code in Plotly.

import datetime
import plotly.express as px

fig = px.bar(df, x=df.index, y="variable", color='value', orientation="h",
             hover_data=[df.index],
             height=350,
             color_continuous_scale=['firebrick', '#2ca02c'],
             title='',
             template='plotly_white', 
            )

The result is just like what I want below.

But, the x-index show numbers. I want a timestamp (month+year) on the x-axis, instead.

Edit Adding the fllowing

fig.update_layout(yaxis=dict(title=''), 
                  xaxis=dict(
                      title='Timestamp', 
                      tickformat = '%Y-%b',
                  )
                 )

Gives

which seems that the x-axis is not read from the data index.

解决方案

If you want to use bars it seems to me that you need to find a nice workaround. Have you considered to use Heatmap?

import pandas as pd
import plotly.graph_objs as go

df = pd.read_csv("availability3.txt",
                 parse_dates=["Timestamp"])
       .drop("Unnamed: 0", axis=1)

# you want to have variable as columns
df = pd.pivot_table(df,
                    index="Timestamp",
                    columns="variable",
                    values="value")
fig = go.Figure()
fig.add_trace(
    go.Heatmap(
        z=df.values.T,
        x=df.index,
        y=df.columns,
        colorscale='RdYlGn',
        xgap=1,
        ygap=2)
      )

fig.show()

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