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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 See http
Step1:  not tested...
writer = pd.ExcelWriter('nd_out.xlsx')
nd.to_excel(writer,'Sheet1')
writer.save()
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Python Code:
from pandas.tools.plotting import scatter_matrix
p = scatter_matrix(nd.loc[:, use_col[:3]], alpha=0.2, figsize=(18, 12), diagonal='kde')
%%script bash --bg --out script_out
bokeh-server
nd.dtypes[:5]
use_col = [True if dtype in ['int64', 'float64'] else False for dtype in nd.dtypes]
from bokeh.crossfilter.models import CrossFilter
from bokeh.sampledata.autompg import autompg
from bokeh.document import Document
from bokeh.session import Session
from bokeh.plotting import *
app = CrossFilter.create(df=nd.loc[:, use_col])
document = Document()
session = Session()
session.use_doc('crossfilter')
session.load_document(document)
document.add(app)
session.store_document(document)
session.show(app)
Explanation: See http://pandas.pydata.org/pandas-docs/stable/visualization.html
End of explanation
nd.to_csv('nd_out.csv')
Explanation: not tested...
writer = pd.ExcelWriter('nd_out.xlsx')
nd.to_excel(writer,'Sheet1')
writer.save()
End of explanation
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