[PYTHON] Where to fix code when using plotly for free
Today's study session was graph visualization, but I found that plotly was really cool, so I will leave a note.
I misunderstood that plotly had to log in, I was told at a study session, but it seemed that I didn't need to register to run it in offline mode. Thank you for telling me.
If you want to try it, please use it with jupyter notebook etc. plotly is on the side of. https://github.com/miyamotok0105/pydata-book/blob/master/ch08-J.ipynb
In the first place, please refer to the graph here. https://qiita.com/alchemist/items/544d45480ce9c1ca2c16
Code fix
It's OK if you modify it to use plotly.offline instead of plotly.plotly </ b>
For example, map mapping modifications
python
import plotly.plotly as py#here
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv')
for col in df.columns:
df[col] = df[col].astype(str)
scl = [[0.0, 'rgb(242,240,247)'],[0.2, 'rgb(218,218,235)'],[0.4, 'rgb(188,189,220)'],\
[0.6, 'rgb(158,154,200)'],[0.8, 'rgb(117,107,177)'],[1.0, 'rgb(84,39,143)']]
df['text'] = df['state'] + '<br>' +\
'Beef '+df['beef']+' Dairy '+df['dairy']+'<br>'+\
'Fruits '+df['total fruits']+' Veggies ' + df['total veggies']+'<br>'+\
'Wheat '+df['wheat']+' Corn '+df['corn']
data = [ dict(
type='choropleth',
colorscale = scl,
autocolorscale = False,
locations = df['code'],
z = df['total exports'].astype(float),
locationmode = 'USA-states',
text = df['text'],
marker = dict(
line = dict (
color = 'rgb(255,255,255)',
width = 2
) ),
colorbar = dict(
title = "Millions USD")
) ]
layout = dict(
title = '2011 US Agriculture Exports by State<br>(Hover for breakdown)',
geo = dict(
scope='usa',
projection=dict( type='albers usa' ),
showlakes = True,
lakecolor = 'rgb(255, 255, 255)'),
)
fig = dict( data=data, layout=layout )
py.iplot( fig, filename='d3-cloropleth-map' )#here
Changed from plotly.plotly to plotly.offline.
# import plotly.plotly as py
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
Changed from py.iplot to iplot.
python
fig = dict( data=data, layout=layout )
#py.iplot( fig, filename='d3-cloropleth-map' )
iplot( fig, filename='d3-cloropleth-map' )
You can change it in this way.
Full text.
python
# import plotly.plotly as py
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv')
for col in df.columns:
df[col] = df[col].astype(str)
scl = [[0.0, 'rgb(242,240,247)'],[0.2, 'rgb(218,218,235)'],[0.4, 'rgb(188,189,220)'],\
[0.6, 'rgb(158,154,200)'],[0.8, 'rgb(117,107,177)'],[1.0, 'rgb(84,39,143)']]
df['text'] = df['state'] + '<br>' +\
'Beef '+df['beef']+' Dairy '+df['dairy']+'<br>'+\
'Fruits '+df['total fruits']+' Veggies ' + df['total veggies']+'<br>'+\
'Wheat '+df['wheat']+' Corn '+df['corn']
data = [ dict(
type='choropleth',
colorscale = scl,
autocolorscale = False,
locations = df['code'],
z = df['total exports'].astype(float),
locationmode = 'USA-states',
text = df['text'],
marker = dict(
line = dict (
color = 'rgb(255,255,255)',
width = 2
) ),
colorbar = dict(
title = "Millions USD")
) ]
layout = dict(
title = '2011 US Agriculture Exports by State<br>(Hover for breakdown)',
geo = dict(
scope='usa',
projection=dict( type='albers usa' ),
showlakes = True,
lakecolor = 'rgb(255, 255, 255)'),
)
fig = dict( data=data, layout=layout )
iplot( fig, filename='d3-cloropleth-map' )
It's cool to be able to make even with a button like this.
There are more samples, so I wonder if I can do it again at a meeting to touch this area. https://plot.ly/python/
See you soon
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