plotly-express-9-plotly实现线型图
plotly-express-9-plotly实现线型图
皮大大
发布于 2021-03-01 15:29:57
发布于 2021-03-01 15:29:57
plotly-express-9-plotly绘制线型图Line
本文中介绍的是利用plotly绘制线型图，使用的是line()和go.Line()方法
With
px.line, each data point is represented as a vertex (which location is given by thexandycolumns) of a polyline mark in 2D space.
导入库
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使用px实现
在plotly_express中是通过px.line方法来实现的
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()
dash中实现
在dash中实现的一个通用方法
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()
使用go.Line实现
官网demo
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
如何给线性图设置风格
# 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()
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, rebeccapurple, saddlebrown, salmon,
sandybrown, seagreen, seashell, sienna, silver,
skyblue, slateblue, slategray, slategrey, snow,
springgreen, steelblue, tan, teal, thistle, tomato,
turquoise, violet, wheat, white, whitesmoke,
yellow, yellowgreenConnect Data Gaps
如果数据中存在缺失值或者说断点，如何处理？
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
如何给图中的某些点添加注释annotions
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
通过一个例子学习如何画出带有填充区域的线型图
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()
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原始发表：2020-6-29，如有侵权请联系 cloudcommunity@tencent.com 删除
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