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Baseline Detection in Python

Learn how to detect baselines on data in Python.

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Imports

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

In [1]:
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.tools import FigureFactory as FF

import numpy as np
import pandas as pd
import scipy
import peakutils

Import Data

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

In [2]:
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')
Out[2]:

Plot with Baseline

In [3]:
# calculate baseline y values
baseline_values = peakutils.baseline(time_series)

trace = go.Scatter(
    x=[j for j in range(len(time_series))],
    y=time_series,
    mode='lines',
    marker=dict(
        color='#B292EA',
    ),
    name='Original Plot'
)

trace2 = go.Scatter(
    x=[j for j in range(len(time_series))],
    y=baseline_values,
    mode='markers',
    marker=dict(
        size=3,
        color='#EB55BF',
        symbol='open-circle'
    ),
    name='Baseline'
)

data = [trace, trace2]
py.iplot(data, filename='milk-production-plot-with-baseline')
Out[3]:
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