plotly-express-10-plotly реализует линейные графики
В этой статье использованиеplotlyЧтобы нарисовать линейный график, используйтеline()иgo.Scatter()метод
With
px.line, each data point is represented as a vertex (which location is given by thexandycolumns) of a polyline mark in 2D space.
библиотека импорта
import pandas as pd
import numpy as np
import plotly_express as px
import plotly.graph_objects as go # 导入go模块
import dash
import dash_core_components as dcc # dash的组件
import dash_html_components as html
Реализовано с помощью px
существуетplotly_expressчерезpx.lineметод достижения
Simple Line Plot with plotly.express
data = px.data.gapminder()
df = data.query("country=='Canada'")
fig = px.line(df, x="year",y="lifeExp",title="Life expectancy in Canada")
fig.show()
Реализовано в тире
Общий метод, реализованный в тире
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )
import dash
import dash_core_components as dcc
import dash_html_components as html
app = dash.Dash()
app.layout = html.Div([
dcc.Graph(figure=fig)
])
app.run_server()
Line Plot with column encoding color
df = px.data.gapminder().query("continent=='Oceania'")
fig = px.line(df, x="year", y="lifeExp", color='country')
fig.show()
Реализовано с помощью go.Scatter
Демонстрация официального сайта
np.random.seed(1)
N = 100
random_x = np.linspace(0, 1, N)
random_y0 = np.random.randn(N) + 5
random_y1 = np.random.randn(N)
random_y2 = np.random.randn(N) - 5
# Create traces
fig = go.Figure()
fig.add_trace(go.Scatter(x=random_x, y=random_y0,
mode='lines',
name='lines'))
fig.add_trace(go.Scatter(x=random_x, y=random_y1,
mode='lines+markers',
name='lines+markers')) # 同时使用线型和点
fig.add_trace(go.Scatter(x=random_x, y=random_y2,
mode='markers', name='markers'))
fig.show()
Style Line Plots
Как оформить линейный график
# Add data
month = ['January', 'February', 'March', 'April', 'May', 'June', 'July',
'August', 'September', 'October', 'November', 'December']
high_2007 = [36.5, 26.6, 43.6, 52.3, 71.5, 81.4, 80.5, 82.2, 76.0, 67.3, 46.1, 35.0]
low_2007 = [23.6, 14.0, 27.0, 36.8, 47.6, 57.7, 58.9, 61.2, 53.3, 48.5, 31.0, 23.6]
high_2014 = [28.8, 28.5, 37.0, 56.8, 69.7, 79.7, 78.5, 77.8, 74.1, 62.6, 45.3, 39.9]
low_2014 = [12.7, 14.3, 18.6, 35.5, 49.9, 58.0, 60.0, 58.6, 51.7, 45.2, 32.2, 29.1]
fig = go.Figure()
# Create and style traces
fig.add_trace(go.Scatter(x=month, y=high_2014, name='High 2014',
line=dict(color='firebrick', width=4))) # 通过line参数设置
fig.add_trace(go.Scatter(x=month, y=low_2014, name = 'Low 2014',
line=dict(color='royalblue', width=4)))
fig.add_trace(go.Scatter(x=month, y=high_2007, name='High 2007',
line=dict(color='firebrick', width=4,
dash='dashdot') # dash options include 'dash', 'dot', and 'dashdot'
))
fig.add_trace(go.Scatter(x=month, y=low_2007, name='Low 2007',
line = dict(color='royalblue', width=4, dash='dot')))
# Edit the layout
fig.update_layout(title='Average High and Low Temperatures in New York', # 左上角的标题设置
xaxis_title='Month', # 横纵坐标的名称
yaxis_title='Temperature (degrees F)')
fig.show()
Connect Data Gaps
Что делать, если в данных есть пропущенные значения или точки останова?
x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
fig = go.Figure()
fig.add_trace(go.Scatter(
x=x,
y=[10, 20, None, 15, 10, 5, 15, None, 20, 10, 10, 15, 25, 20, 10],
name = '<b>No</b> Gaps', # Style name/legend entry with html tags：使用HTML标签给图例或者名字进行格式设置
connectgaps=True # override default to connect the gaps 断点连接起来
))
fig.add_trace(go.Scatter(
x=x,
y=[5, 15, None, 10, 5, 0, 10, None, 15, 5, 5, 10, 20, 15, 5],
name='Gaps',
))
fig.update_layout(title="How to deal with the missing data with plot") # 图例
fig.show()
Label Lines with Annotations
Как аннотировать определенные точки на графикеannotions
fig = go.Figure()
fig.add_trace(go.Scatter(
x=[0, 1, 2, 3, 4, 5, 6, 7, 8],
y=[0, 1, 3, 2, 4, 3, 4, 6, 5],
name = "Line-1" # 将右上角的标签进行修改
))
fig.add_trace(go.Scatter(
x=[0, 1, 2, 3, 4, 5, 6, 7, 8],
y=[0, 4, 5, 1, 2, 2, 3, 4, 2],
name = "Line-2"
))
fig.add_annotation(
x=2, # 给（2.5） 给特殊点添加注解
y=5,
text="max number")
fig.add_annotation(
x=4,
y=4,
text="median number")
fig.update_annotations(dict(
xref="x",
yref="y",
showarrow=True,
arrowhead=7,
ax=0,
ay=-40
))
fig.update_layout(showlegend=True) # 显示图例
fig.show()
Filled Lines
Узнайте, как нарисовать линейный график с закрашенными областями на примере
x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
x_rev = x[::-1] # 翻转的数据
# Line 1
y1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
y1_upper = [2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
y1_lower = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
y1_lower = y1_lower[::-1]
# Line 2
y2 = [5, 2.5, 5, 7.5, 5, 2.5, 7.5, 4.5, 5.5, 5]
y2_upper = [5.5, 3, 5.5, 8, 6, 3, 8, 5, 6, 5.5]
y2_lower = [4.5, 2, 4.4, 7, 4, 2, 7, 4, 5, 4.75]
y2_lower = y2_lower[::-1]
fig = go.Figure()
# 第一条线的填充区域
fig.add_trace(go.Scatter(
x = x + x_rev,
y = y1_upper + y1_lower,
fill = 'toself', # 显示填充
fillcolor = 'rgba(0,100,80,0.2)', # 填充区域颜色
line_color = 'rgba(255,255,255,0)', # 边界颜色
showlegend = False,
name = 'Fair',
))
fig.add_trace(go.Scatter(
x = x + x_rev,
y = y2_upper + y2_lower,
fill = 'toself',
fillcolor = 'rgba(231,107,243,0.2)',
line_color = 'rgba(255,255,255,0)',
name = 'Premium',
showlegend = False,
))
# 画两条线
fig.add_trace(go.Scatter(
x=x, y=y1,
line_color='rgb(0,100,80)',
name='Fair',
))
fig.add_trace(go.Scatter(
x=x, y=y2,
line_color='rgb(231,107,243)',
name='Premium',
))
# fig.update_traces(mode='lines')
fig.show()