Plotly:如何设置自定义 xticks

本文介绍了Plotly:如何设置自定义 xticks的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！

问题描述

来自

由于 x_dates[::2] 的长度是 50 ，ticknumber 根本不匹配.我如何解决它??

解决方案

我通常使用下面的方法.您应该知道 tickvals 将被视为一个位置参数，并且最适合(可能仅)用于数值而不是日期.使用 ticktext 以您喜欢的格式显示日期.

片段 1:

fig.update_xaxes(tickangle=45,滴答模式 = '数组',tickvals = df_tips['date'][0::40],ticktext= [d.strftime('%Y-%m-%d') for d in datelist])

情节 1:

现在您可以将 tickvals=np.arange(0, y.shape[0]).astype(int)[0::40] 更改为 tickvals=np.arange(0, y.shape[0]).astype(int)[0::80] 并得到:

情节 2:

那么为什么这第一次对您不起作用?几个原因:

您重新采样的 pandas 系列 y 将日期作为索引，因此 y.index 被设置为 x-轴值.
y.index 返回日期
当您通过 fig.update_xaxes(tickvals) 设置刻度线 positions 时，这对整数值效果更好.

我做了什么来修复它?

我在重新采样后重置了索引，以便 y.index 不返回日期.
使用 .to_frame 将 y 更改为数据帧.
更改为 fig.add_trace(go.Scatter(x=y.index, y=yy)) 否则会失败，因为这现在是数据帧而不是系列.
您的日期现在检索为 x_dates = y.ds

我知道 y=yy 看起来真的很奇怪，但我只是把它留下来作为一个友好的提醒，让你的 Pandas 系列或数据框比单个名称更合理像 y 这样的字母更容易与单个、无索引的数组或列表混淆.

完整代码:

将pandas导入为pd将 numpy 导入为 np导入 plotly.graph_objects as go导入 plotly.offline 作为 py导入 plotly.express 作为 px从 plotly.offline 导入 init_notebook_mode# 数据np.random.seed(42)特征 = pd.DataFrame({'ds': pd.date_range('20200101', period=100*24, freq='H'),'y': np.random.randint(0,20, 100*24) ,'yhat': np.random.randint(0,20, 100*24) ,'价格':np.random.choice([6600, 7000, 5500, 7800], 100*24)})# 重采样y = feature.set_index('ds').resample('D')['y'].sum()#.to_frame()y=y.to_frame()y.reset_index(就地=真)# 情节设置fig = go.Figure()fig.add_trace(go.Scatter(x=y.index, y=y.y))# x-ticks 准备x_dates = y.dstickvals=np.arange(0, y.shape[0]).astype(int)[0::40]滴答文本=x_dates# 更新标记fig.update_xaxes(tickangle=45,滴答模式 = '数组',滴答=滴答，ticktext=[d.strftime('%Y-%m-%d') for d in ticktext])图.show()

From plotly doc:

Example:

import pandas as pd
import numpy as np

np.random.seed(42)
feature = pd.DataFrame({'ds': pd.date_range('20200101', periods=100*24, freq='H'),
                        'y': np.random.randint(0,20, 100*24) ,
                        'yhat': np.random.randint(0,20, 100*24) ,
                        'price': np.random.choice([6600, 7000, 5500, 7800], 100*24)})


import plotly.graph_objects as go
import plotly.offline as py
import plotly.express as px
from plotly.offline import init_notebook_mode

init_notebook_mode(connected=True)


y = feature.set_index('ds').resample('D')['y'].sum()

fig = go.Figure()
fig.add_trace(go.Scatter(x=y.index, y=y))


x_dates = y.index.to_series().dt.strftime('%Y-%m-%d').sort_values().unique()


layout = dict(
    xaxis=dict(
        tickmode="array",
        tickvals=np.arange(0, x_dates.shape[0],2).astype(int),
        ticktext=x_dates[::2],
        tickformat='%Y-%m-%d',
        tickangle=45,
    )
)

fig.update_layout(layout)
fig.show()

Result:

Since length of x_dates[::2] is 50 , the ticknumber doesn't match at all .How do I sovle it ??

解决方案

I normally use the approach below. You should know that tickvals is to be regarded as a positional argument and works best (perhaps only) with numerical values and not dates. Use ticktext to display the dates in your preferred format.

Snippet 1:

fig.update_xaxes(tickangle=45,
                 tickmode = 'array',
                 tickvals = df_tips['date'][0::40],
                 ticktext= [d.strftime('%Y-%m-%d') for d in datelist])

Plot 1:

Now you can change tickvals=np.arange(0, y.shape[0]).astype(int)[0::40] to tickvals=np.arange(0, y.shape[0]).astype(int)[0::80] and get:

Plot 2:

So why didn't this work for you the first time? A number of reasons:

Your resampled pandas series y had dates as indexes, so y.index were set as x-axis values.
y.index returns dates
When you set the tickmark positions through fig.update_xaxes(tickvals), this works better with integer values.

And what did I do to fix it?

I reset the index after resampling so that y.index does not return dates.
Changed y to a dataframe using .to_frame.
Changed to fig.add_trace(go.Scatter(x=y.index, y=y.y)) which otherwise would have failed since this is now a dataframe and not a series.
Your dates are now retrieved as x_dates = y.ds

I know y=y.y looks really weird, but I just left it like that as a friendly reminder to give your pandas series or dataframes more sensible names than a single letter like y that's more likely to be confused with a single, index-free, array or list.

Complete code:

import pandas as pd
import numpy as np
import plotly.graph_objects as go
import plotly.offline as py
import plotly.express as px
from plotly.offline import init_notebook_mode

# data
np.random.seed(42)
feature = pd.DataFrame({'ds': pd.date_range('20200101', periods=100*24, freq='H'),
                        'y': np.random.randint(0,20, 100*24) ,
                        'yhat': np.random.randint(0,20, 100*24) ,
                        'price': np.random.choice([6600, 7000, 5500, 7800], 100*24)})

# resampling
y = feature.set_index('ds').resample('D')['y'].sum()#.to_frame()
y=y.to_frame()
y.reset_index(inplace=True)

# plotly setup
fig = go.Figure()
fig.add_trace(go.Scatter(x=y.index, y=y.y))

# x-ticks preparations
x_dates = y.ds
tickvals=np.arange(0, y.shape[0]).astype(int)[0::40]
ticktext=x_dates

# update tickmarks
fig.update_xaxes(tickangle=45,
                 tickmode = 'array',
                 tickvals = tickvals,
                 ticktext=[d.strftime('%Y-%m-%d') for d in ticktext])

fig.show()

这篇关于Plotly:如何设置自定义 xticks的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！

With

Plotly:如何设置自定义 xticks

问题描述