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Baseline Detection in Python

Learn how to detect baselines on data in Python.

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Plotly's Python library is free and open source! Get started by downloading the client and reading the primer.
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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
import plotly.figure_factory 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='circle-open'
    ),
    name='Baseline'
)

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