数据可视化---plotly篇
plotly
https://plot.ly/python/ plotly是现代平台的敏捷商业智能和数据科学库，它作为一款开源的绘图库，可以应用于Python、R、MATLAB、Excel、JavaScript和jupyter等多种语言，主要使用的js进行图形绘制，实现过程中主要就是调用plotly的函数接口，底层实现完全被隐藏，便于初学者的掌握。
Basic Example
In [6]:
import plotly.plotly as py
import plotly.graph_objs as go
py.sign_in('deamoncao', '*******') # 注意：这里是plotly网站的用户名和密码
trace = go.Bar(x=[2, 4, 6], y= [10, 12, 15])
data = [trace]
layout = go.Layout(title='A Simple Plot', width=800, height=640)
fig = go.Figure(data=data, layout=layout)
py.image.save_as(fig, filename='a-simple-plot.png')
from IPython.display import Image
Image('a-simple-plot.png')
Out[6]:
In [22]:
import plotly.plotly as py
import plotly.graph_objs as go
import numpy as np
y0 = np.random.randn(50)-1
y1 = np.random.randn(50)+1
trace0 = go.Box(
y=y0
)
trace1 = go.Box(
y=y1
)
data = [trace0, trace1]
py.iplot(data)
Out[22]:
In [9]:
import plotly.plotly as py
import plotly.graph_objs as go
x_data = ['Carmelo Anthony', 'Dwyane Wade',
'Deron Williams', '* Lopez',
'Damian Lillard', 'David West',]
y0 = np.random.randn(50)-1
y1 = np.random.randn(50)+1
y2 = np.random.randn(50)
y3 = np.random.randn(50)+2
y4 = np.random.randn(50)-2
y5 = np.random.randn(50)+3
y_data = [y0,y1,y2,y3,y4,y5]
colors = ['rgba(93, 164, 214, 0.5)', 'rgba(255, 144, 14, 0.5)', 'rgba(44, 160, 101, 0.5)', 'rgba(255, 65, 54, 0.5)', 'rgba(207, 114, 255, 0.5)', 'rgba(127, 96, 0, 0.5)']
traces = []
for xd, yd, cls in zip(x_data, y_data, colors):
traces.append(go.Box(
y=yd,
name=xd,
boxpoints='all',
jitter=0.5,
whiskerwidth=0.2,
fillcolor=cls,
marker=dict(
size=2,
),
line=dict(width=1),
))
layout = go.Layout(
title='Points Scored by the Top 9 Scoring NBA Players in 2012',
yaxis=dict(
autorange=True,
showgrid=True,
zeroline=True,
dtick=5,
gridcolor='rgb(255, 255, 255)',
gridwidth=1,
zerolinecolor='rgb(255, 255, 255)',
zerolinewidth=2,
),
margin=dict(
l=40,
r=30,
b=80,
t=100,
),
paper_bgcolor='rgb(243, 243, 243)',
plot_bgcolor='rgb(243, 243, 243)',
showlegend=False
)
fig = go.Figure(data=traces, layout=layout)
py.iplot(fig)
Out[9]:
In [23]:
import plotly.plotly as py
import pandas as pd
df_airports = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_february_us_airport_traffic.csv')
df_airports.head()
df_flight_paths = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_february_aa_flight_paths.csv')
df_flight_paths.head()
airports = [ dict(
type = 'scattergeo',
locationmode = 'USA-states',
lon = df_airports['long'],
lat = df_airports['lat'],
hoverinfo = 'text',
text = df_airports['airport'],
mode = 'markers',
marker = dict(
size=2,
color='rgb(255, 0, 0)',
line = dict(
width=3,
color='rgba(68, 68, 68, 0)'
)
))]
flight_paths = []
for i in range( len( df_flight_paths ) ):
flight_paths.append(
dict(
type = 'scattergeo',
locationmode = 'USA-states',
lon = [ df_flight_paths['start_lon'][i], df_flight_paths['end_lon'][i] ],
lat = [ df_flight_paths['start_lat'][i], df_flight_paths['end_lat'][i] ],
mode = 'lines',
line = dict(
width = 1,
color = 'red',
),
opacity = float(df_flight_paths['cnt'][i])/float(df_flight_paths['cnt'].max()),
)
)
layout = dict(
title = 'Feb. 2011 American Airline flight paths<br>(Hover for airport names)',
showlegend = False,
geo = dict(
scope='north america',
projection=dict( type='azimuthal equal area' ),
showland = True,
landcolor = 'rgb(243, 243, 243)',
countrycolor = 'rgb(204, 204, 204)',
),
)
fig = dict( data=flight_paths + airports, layout=layout )
py.iplot( fig, filename='d3-flight-paths' )
Out[23]:
In [24]:
import plotly.plotly as py
import pandas as pd
try:
# Python 2
from itertools import izip
except ImportError:
# Python 3
izip = zip
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/globe_contours.csv')
df.head()
contours = []
scl = ['rgb(213,62,79)','rgb(244,109,67)','rgb(253,174,97)',\
'rgb(254,224,139)','rgb(255,255,191)','rgb(230,245,152)',\
'rgb(171,221,164)','rgb(102,194,165)','rgb(50,136,189)']
def pairwise(iterable):
a = iter(iterable)
return izip(a, a)
i=0
for lat, lon in pairwise(df.columns):
contours.append( dict(
type = 'scattergeo',
lon = df[lon],
lat = df[lat],
mode = 'lines',
line = dict(
width = 2,
color = scl[i]
)
) )
i = 0 if i+1 >= len(df.columns)/4 else i+1
layout = dict(
title = 'Contour lines over globe<br>(Click and drag to rotate)',
showlegend = False,
geo = dict(
showland = True,
showlakes = True,
showcountries = True,
showocean = True,
countrywidth = 0.5,
landcolor = 'rgb(230, 145, 56)',
lakecolor = 'rgb(0, 255, 255)',
oceancolor = 'rgb(0, 255, 255)',
projection = dict(
type = 'orthographic',
rotation = dict(
lon = -100,
lat = 40,
roll = 0
)
),
lonaxis = dict(
showgrid = True,
gridcolor = 'rgb(102, 102, 102)',
gridwidth = 0.5
),
lataxis = dict(
showgrid = True,
gridcolor = 'rgb(102, 102, 102)',
gridwidth = 0.5
)
)
)
fig = dict( data=contours, layout=layout )
py.iplot( fig, validate=False, filename='d3-globe' )
Out[24]: