#!/usr/bin/env python
# coding: utf-8

# # A Preview

# A quick look at some examples indicating the sorts of things that will be examined in later notebooks.
# 
# Each notebook will take advantage of the *NbAgg* backend, and we set that up first:

# In[1]:


import matplotlib
matplotlib.use('nbagg')
get_ipython().run_line_magic('matplotlib', 'inline')


# Next we'll do whatever imports we will need for the session:

# In[2]:


import matplotlib.pyplot as plt
import matplotlib.colors as colors
import seaborn as sns 
import numpy as np
from scipy import stats 
import pandas as pd 


# ## Joint Plots with Seaborn

# As you can see from the import, we're going to use Seaborn for some nice visual presentation. Let's select a [palette](http://web.stanford.edu/~mwaskom/software/seaborn/tutorial/color_palettes.html) and color saturation level:

# In[3]:


sns.set_palette("BuPu_d")
sns.set_context("notebook", font_scale=2.0)


# We're also going to use NumPy and SciPy to generate some data. Next, let's get some Seaborn defaults set up:

# In[4]:


np.random.seed(42424242)


# Let's create some random data to use for our visualization:

# In[5]:


x = stats.gamma(5).rvs(420)
y = stats.gamma(13).rvs(420)


# And now, let's plot the data:

# In[6]:


with sns.axes_style("white"):
    sns.jointplot(x, y, kind="hex", size=16)


# ## Scatter Plot Matrix Graphs with Pandas

# Our next preview will be a Pandas teaser displaying a great deal of data in a single plot. The Pandas project ships with some sample data that we can load and view:

# In[7]:


baseball = pd.read_csv("../data/baseball.csv") 


# Pandas uses the new "ggplot" style defined in matplotlib. We'd like to override that with a custom style sheet based on the palette we've chosen from Seaborn. Let's get the list of colors from our palette:

# In[8]:


[colors.rgb2hex(x) for x in sns.color_palette()]


# To see how we used some of these colors, take a look at ``./styles/custom.mplstyle``.
# 
# Now let's graph our data, using the custom style that changes the default background color used by pandas (from the 'ggplot' style):

# In[9]:


plt.style.use('../styles/custom.mplstyle')
data = pd.scatter_matrix(baseball.loc[:,'r':'sb'], figsize=(16, 10))