baseline-subtraction.md

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jupytext kernelspec plotly notebook_metadata_filter text_representation all extension format_name format_version jupytext_version .md markdown 1.1 1.1.1 display_name language name Python 2 python python2 description display_as has_thumbnail language layout name order page_type permalink thumbnail Learn how to subtract baseline estimates from data in Python. peak-analysis false python base Baseline Subtraction 2 example_index python/baseline-subtraction/ /images/static-image

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Imports

The tutorial below imports NumPy, Pandas, SciPy and PeakUtils.

importplotly.plotlyaspyimportplotly.graph_objsasgoimportplotly.toolsastoolsimportplotly.figure_factoryasffimportnumpyasnpimportpandasaspdimportscipyimportpeakutils

Import Data

As with our baseline detection example, we will import some data on milk production by month:

milk_data=pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/monthly-milk-production-pounds.csv') time_series=milk_data['Monthly milk production (pounds per cow)'] time_series=np.asarray(time_series) df=milk_data[0:15] table=ff.create_table(df) py.iplot(table, filename='milk-production-dataframe')

Plot with Baseline

To subtract a baseline estimate from our data, it is a good idea to first we must first calculate the baseline values then plot the data with the baseline drawn in.

baseline_values=peakutils.baseline(time_series) trace=go.Scatter( x=[jforjinrange(len(time_series))], y=time_series, mode='lines', marker=dict( color='#547C66', ), name='Original Plot' ) trace2=go.Scatter( x=[jforjinrange(len(time_series))], y=baseline_values, mode='markers', marker=dict( size=3, color='#EB55BF', symbol='circle-open' ), name='Baseline' ) data= [trace, trace2] py.iplot(data, filename='milk-production-plot-with-baseline')

Baseline Subtraction

baseline_values=peakutils.baseline(time_series) trace=go.Scatter( x=[jforjinrange(len(time_series))], y=time_series, mode='lines', marker=dict( color='#547C66', ), name='Original Plot' ) trace2=go.Scatter( x=[jforjinrange(len(time_series))], y=baseline_values, mode='markers', marker=dict( size=3, color='#EB55BF', symbol='circle-open' ), name='Baseline' ) data= [trace, trace2] py.iplot(data, filename='milk-production-plot-with-baseline')

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