[英]How to show timestamp x-axis in Python Plotly
I want to plot this data to evaluate data availability.我想绘制此数据以评估数据可用性。 I used the following plotting code in Plotly.
我在 Plotly 中使用了以下绘图代码。
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.结果就像我在下面想要的一样。
But, the x-index show numbers.但是,x-index 显示数字。 I want a timestamp (month+year) on the x-axis, instead.
我想要一个在 x 轴上的时间戳(月 + 年),而不是。
Edit Adding the fllowing编辑添加流动
fig.update_layout(yaxis=dict(title=''),
xaxis=dict(
title='Timestamp',
tickformat = '%Y-%b',
)
)
Gives给
which seems that the x-axis is not read from the data index.这似乎不是从数据索引中读取 x 轴。
If you want to use bars it seems to me that you need to find a nice workaround.如果你想使用酒吧,在我看来你需要找到一个很好的解决方法。 Have you considered to use
Heatmap
?你考虑过使用
Heatmap
吗?
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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