Plotlywrapper Demo Notebook

Welcome! This notebook demonstrates plotlywrapper's API.



In [1]:

    
import plotlywrapper as pw
import pandas as pd
import numpy as np
from numpy import random as rng

Now we need to generate some data to plot.



In [2]:

    
n = 100
X = rng.randn(100, 3)
df = pd.DataFrame(X, pd.date_range('2016', periods=n, freq=pd.DateOffset(hours=1)), columns=['alpha', 'beta', 'gamma'])

We can create scatter plots with scatter or df.plotly.scatter.



In [3]:

    
df.plotly.scatter()









    











    











    Out[3]:





<plotlywrapper._Chart object at 0x11d692ac8>

We can create bar charts with bar or df.plotly.bar.



In [4]:

    
df.plotly.bar()









    











    











    Out[4]:





<plotlywrapper._Chart object at 0x11cc31438>

We can can show plots together simple by adding them.



In [5]:

    
plot = df.plotly.bar()
plot += df.plotly.line(opacity=0.7)
plot.ylabel('deliciousness')
plot.xlabel('xlabel')









    











    











    Out[5]:





<plotlywrapper._Chart object at 0x11d07c400>



In [6]:

    
plot = pw.fill_between(ylow=X[:, 0], yhigh=X[:, 1])
plot += pw.fill_zero(X[:, 2])
plot









    











    











    Out[6]:





<plotlywrapper._Chart object at 0x11d3347b8>

You can also make 3D plots!



In [7]:

    
def fxy(x, y):
    A = 1  # choose a maximum amplitude 
    return A*(np.cos(np.pi*x*y))**2 * np.exp(-(x**2+y**2)/2.)
L = 4
x = y = np.arange(-L/2., L/2., 0.1)  # use a mesh spacing of 0.1
z = fxy(x, y[:, None])

pw.surface(x, y, z)









    











    











    Out[7]:





<plotlywrapper._Chart object at 0x11d334390>



In [8]:

    
t = np.linspace(0, 4*np.pi)
x = np.sin(t)
y = np.cos(t)
x2 = np.sin(t - np.pi)
y2 = np.cos(t - np.pi)

pw.line3d(x, y, t, width=20) + pw.line3d(x2, y2, t, width=20)









    











    











    Out[8]:





<plotlywrapper._Chart object at 0x11d07ce48>

To learn more take a look at the source!