Python 官方文档:入门教程 => 点击学习
目录一、整理数据二、折线图三、散点图四、饼图五、柱形图六、点图(设置多个Go对象)七、2D密度图八、简单3D图一、整理数据 以300部电影作为数据源 import pandas as
以300部电影作为数据源
cnboo
import seaborn as sns
import numpy as np
import matplotlib as mpl
from matplotlib import pyplot as plt
import pandas as pd
from datetime import datetime,timedelta
%matplotlib inline
plt.rcParams['font.sans-serif']=['SimHei'] # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus']=False # 用来正常显示负号
from datetime import datetime
! pip install plotly # 安装
import matplotlib.pyplot as plt
import plotly
from plotly.offline import download_plotlyjs,init_notebook_mode,plot,iplot
x=cnboo['BO'].tolist()
y=cnboo['PERSONS'].tolist()
dict01={"x":x,"y":y}
dict01
# 折线图
iplot([dict01])
import plotly.graph_objs as go
iplot([go.Scatter(x=x,y=y,mode='markers')])
# 随机生成的点图
import numpy as np
iplot([go.Scatter(x=np.random.randn(100),y=np.random.randn(100),mode='markers')])
go
trace=go.Scatter(x=cnboo['PRICE'],y=y,mode='markers',)
data=[trace]
iplot(data)
trace=go.Scatter(x=cnboo['PRICE'],y=y,mode='markers',marker=dict(color='red',size=9,opacity=0.4))
data=[trace]
iplot(data)
colors=['#dc2624','#2b4750','#45a0a2','#e87a59','#7dcaa9','#649E7D','#dc8018',
'#C89F91','#6c6d6c','#4f6268','#c7cccf']
filmtype=cnboo['TYPE']
filmbo=cnboo['PRICE']
trace=go.Pie(labels=filmtype,values=filmbo,
hoverinfo='label+percent',textinfo='value',textfont=dict(size=10),
marker=dict(colors=colors,line=dict(color='#000000',width=3)))
data=[trace]
iplot(data)
filmtype=cnboo['TYPE']
filmbo=cnboo['PRICE']
trace=go.Pie(labels=filmtype,values=filmbo,
hoverinfo='label+percent',textinfo='value',textfont=dict(size=12),
marker=dict(colors=colors))
data=[trace]
iplot(data)
# plotly bar
trace1=go.Bar(x=cnboo['TYPE'],y=cnboo['PRICE'],name="类型与票价")
trace2=go.Bar(x=cnboo['TYPE'],y=y,name="类型与人数")
layout=go.Layout(title="中国电影类型与票价,人数的关系",xaxis=dict(title='电影类型'))
data=[trace1,trace2]
fig=go.Figure(data,layout=layout)
iplot(fig)
trace1=go.Scatter(x=cnboo['TYPE'],y=cnboo['PRICE'],name="类型与票价",mode="markers",
marker=dict(color="red",size=8))
trace2=go.Scatter(x=cnboo['TYPE'],y=cnboo['PERSONS'],name="类型与人数",mode="markers",
marker=dict(color="blue",size=5))
data=[trace1,trace2]
iplot(data)
trace1=go.Scatter(x=cnboo['TYPE'],y=cnboo['PRICE'],name="类型与票价",mode="markers",
marker=dict(color="red",size=8))
trace2=go.Scatter(x=cnboo['TYPE'],y=cnboo['PERSONS'],name="类型与人数",mode="markers",
marker=dict(color="blue",size=5))
layout=go.Layout(title="中国电影类型与票价,人数的关系",plot_bGColor="#FFFFFF")
data=[trace1,trace2]
fig=go.Figure(data,layout=layout)
iplot(fig)
import plotly.figure_factory as ff
fig=ff.create_2d_density(x,y,colorscale=colors,hist_color='#dc2624',point_size=5)
iplot(fig,filename='评分与人次')
colorscale=['rgb(20, 38, 220)',
'rgb(255, 255, 255)'] # 最后一个颜色都是调用背景
fig=ff.create_2d_density(x,y,colorscale=colorscale,hist_color='#dc2624',point_size=5)
iplot(fig,filename='评分与人次')
layout=go.Layout(title="中国电影票房与人次,票价的关系",barmode="group")
trace01=go.Scatter3d(
x=cnboo['BO'],
y=cnboo['PRICE'],
z=cnboo['PERSONS'],
mode='markers',
marker=dict(size=12,color=colors,colorscale='Viridis',
opacity=0.5,showscale=True) #opacity是透明度
)
data=[trace01]
fig=go.Figure(data=data,layout=layout)
iplot(fig,filename='3d')
以上就是python matplotlib plotly绘制图表详解的详细内容,更多关于Python matplotlib plotly的资料请关注编程网其它相关文章!
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