1/简介
数据分析离不开数据可视化。
我们最常用的开源组件(技术库)有pandas,matplotlib,pyecharts,tableau。
plotly是最新的用来做数据可视化的开源组件。
plotly是一款用来做数据分析和数据可视化的在线平台,功能很强大,可以绘制出很多图形。
比如条形图,散点图,饼图,柱状图等。
还支持在线编辑,可以支持多种语言,比如python,javascript,matlab,R语言等。
推荐使用jupyter notebook,不推荐使用pycharm,因为在pycharm中操作不方便。

2/如何安装plotly
pip install plotly
3/绘制图
<1>折线图
from plotly.graph_objs import Scatter,Layout
import plotly
import plotly.offline as py
import numpy as np
import plotly.graph_objs as go
plotly.offline.init_notebook_mode(connected=True)
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
trace0 = go.Scatter(
x = random_x,
y = random_y0,
mode = 'markers',
name = 'markers'
)
trace1 = go.Scatter(
x = random_x,
y = random_y1,
mode = 'lines+markers',
name = 'lines+markers'
)
trace2 = go.Scatter(
x = random_x,
y = random_y2,
mode = 'lines',
name = 'lines'
)
data = [trace0,trace1,trace2]
py.iplot(data)

<2>散点图
from plotly.graph_objs import Scatter,Layout
import plotly
import plotly.offline as py
import numpy as np
import plotly.graph_objs as go
plotly.offline.init_notebook_mode(connected=True)
trace1 = go.Scatter(
y = np.random.randn(500),
mode = 'markers',
marker = dict(size = 16,
color = np.random.randn(500),
colorscale = 'Viridis',
showscale = True
)
)
data = [trace1]
py.iplot(data)

<3>直方图
from plotly.graph_objs import Scatter,Layout
import plotly
import plotly.offline as py
import numpy as np
import plotly.graph_objs as go
plotly.offline.init_notebook_mode(connected=True)
trace0 = go.Bar(
x = ['Jan','Feb','Mar','Apr', 'May','Jun',
'Jul','Aug','Sep','Oct','Nov','Dec'],
y = [20,14,25,16,18,22,19,15,12,16,14,17],
name = 'Primary Product',
marker=dict(
color = 'rgb(49,130,189)'
)
)
trace1 = go.Bar(
x = ['Jan','Feb','Mar','Apr', 'May','Jun',
'Jul','Aug','Sep','Oct','Nov','Dec'],
y = [19,14,22,14,16,19,15,14,10,12,12,16],
name = 'Secondary Product',
marker=dict(
color = 'rgb(204,204,204)'
)
)
data = [trace0,trace1]
py.iplot(data)
