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Added Polynomial Fit, and linear fit examples for python
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‎_includes/documentation_eg.html

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{% assign financial_analysis = true %}
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{% elsif page.display_as == "multiple_axes" %}
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{% assign multiple_axes = true %}
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{% elsif page.display_as == "fitting_tools" %}
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{% assign fitting_tools = true %}
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{% elsif page.display_as == "scientific" %}
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{% assign scientific = true %}
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{% elsif page.display_as == "statistical" %}
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</div>
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{% endif %}
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{% if fitting_tools %}
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<hr>
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<h4 class="example-section-title" id="fitting-tools"><a class="no_underline plot-blue" href="#fitting-tools">Fitting Tools</a></h4>
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<div class="row">
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{% for page in languagelistimg %}
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{% if page.display_as == "fitting_tools" %}
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<a href="/{{page.permalink}}">
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<div class="alltutcol">
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<img class="thumbnail" alt="{{page.name}}" src="{{site.imgurl}}{{page.thumbnail}}" >
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<div class="titlecenter">
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<h5 class="centered"> {{page.name}} </h5>
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</div>
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</div>
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</a>
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<div class="{% cycle 'group2-clear': '', '', 'three-column-clear' %}"></div>
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<div class="{% cycle 'group 2': '', '', 'three-column-clear', '', 'five-column-clear' %}"></div>
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{% endif %}
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{% endfor %}
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</div>
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{% endif %}
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{% if page.language == "matlab" or page.language == "python" %}
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<hr>
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<h4 class="example-section-title" id="streaming"><a class="no_underline plot-blue" href="#streaming">Streaming</a></h4>

‎_posts/python/linear-fit/2015-12-13-linear-fit-python_index.html

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---
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title: Linear fit in Python | Examples | Plotly
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name: Linear Fit
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permalink: python/linear-fits/
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description: Create a polynomial fit / regression in Python and add a line of best fit to your chart
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layout: base
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thumbnail: thumbnail/linear_fit.jpg
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language: python
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page_type: example_index
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has_thumbnail: true
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display_as: fitting_tools
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---
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{% assign examples = site.posts | where:"language","python" | where:"suite","linear_fit" | sort: "order" %}
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{% include auto_examples.html examples=examples %}

‎_posts/python/linear-fit/2015-12-13-linear-fit.html

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---
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name: Linear fit
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plot_url: https://plot.ly/~tarzzz/870
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language: python
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suite: linear_fit
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order: 0
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sitemap: false
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---
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# Learn about API authentication here: https://plot.ly/python/getting-started
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# Find your api_key here: https://plot.ly/settings/api
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import plotly.plotly as py
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import plotly.graph_objs as go
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# Scientific libraries
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from numpy import arange,array,ones
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from scipy import stats
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xi = arange(0,9)
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A = array([ xi, ones(9)])
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# (Almost) linear sequence
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y = [19, 20, 20.5, 21.5, 22, 23, 23, 25.5, 24]
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# Generated linear fit
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slope, intercept, r_value, p_value, std_err = stats.linregress(xi,y)
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line = slope*xi+intercept
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# Creating the dataset, and generating the plot
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trace1 = go.Scatter(
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x=xi,
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y=y,
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mode='markers',
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marker=go.Marker(color='rgb(255, 127, 14)')
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)
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trace2 = go.Scatter(
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x=xi,
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y=line,
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mode='lines',
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marker=go.Marker(color='rgb(31, 119, 180)')
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)
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annotation = go.Annotation(
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x=3.5,
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y=23.5,
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text='$R^2 = 0.9551,\\Y = 0.716X + 19.18$',
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showarrow=False
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# font=go.Font(size=18)
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)
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layout = go.Layout(
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title='Linear Fit in Python',
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plot_bgcolor='rgb(229, 229, 229)',
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xaxis=go.XAxis(zerolinecolor='rgb(255,255,255)', gridcolor='rgb(255,255,255)'),
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yaxis=go.YAxis(zerolinecolor='rgb(255,255,255)', gridcolor='rgb(255,255,255)'),
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annotations=[annotation]
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)
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data = [trace1, trace2]
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fig = go.Figure(data=data, layout=layout)
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py.plot(fig, filename='Linear-Fit-in-python')

‎_posts/python/polynomial-fit/2015-12-13-polynomial-fit-python_index.html

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---
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title: Polynomial fit in Python | Examples | Plotly
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name: Polynomial Fit
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permalink: python/polynomial-fits/
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description: Create a polynomial fit / regression in Python and add a line of best fit to your chart
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layout: base
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thumbnail: thumbnail/polynomial_fit.jpg
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language: python
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page_type: example_index
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has_thumbnail: true
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display_as: fitting_tools
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---
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{% assign examples = site.posts | where:"language","python" | where:"suite","polynomial_fit" | sort: "order" %}
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{% include auto_examples.html examples=examples %}

‎_posts/python/polynomial-fit/2015-12-13-polynomial-fit.html

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---
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name: Polynomial fit
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plot_url: https://plot.ly/~tarzzz/895
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language: python
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suite: polynomial_fit
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order: 0
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description: Inspired by <a href="http://stackoverflow.com/a/19165440">Stack Overflow</a>.
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sitemap: false
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---
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# Learn about API authentication here: https://plot.ly/python/getting-started
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# Find your api_key here: https://plot.ly/settings/api
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import plotly.plotly as py
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import plotly.graph_objs as go
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# Scientific libraries
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import numpy as np
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points = np.array([(1, 1), (2, 4), (3, 1), (9, 3)])
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# get x and y vectors
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x = points[:,0]
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y = points[:,1]
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# calculate polynomial
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z = np.polyfit(x, y, 3)
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f = np.poly1d(z)
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print f
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# calculate new x's and y's
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x_new = np.linspace(x[0], x[-1], 50)
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y_new = f(x_new)
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# Creating the dataset, and generating the plot
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trace1 = go.Scatter(
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x=x,
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y=y,
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mode='markers',
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marker=go.Marker(color='rgb(255, 127, 14)')
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)
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trace2 = go.Scatter(
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x=x_new,
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y=y_new,
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mode='lines',
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marker=go.Marker(color='rgb(31, 119, 180)')
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)
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annotation = go.Annotation(
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x=6,
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y=-4.5,
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text='$\textbf{Fit}: 0.43X^3 - 0.56X^2 + 16.78X + 10.61$',
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showarrow=False
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# font=go.Font(size=18)
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)
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layout = go.Layout(
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title='Polynomial Fit in Python',
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plot_bgcolor='rgb(229, 229, 229)',
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xaxis=go.XAxis(zerolinecolor='rgb(255,255,255)', gridcolor='rgb(255,255,255)'),
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yaxis=go.YAxis(zerolinecolor='rgb(255,255,255)', gridcolor='rgb(255,255,255)'),
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annotations=[annotation]
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)
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data = [trace1, trace2]
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fig = go.Figure(data=data, layout=layout)
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py.plot(fig, filename='Polynomial-Fit-in-python')

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