#!/bin/python

# -*- coding: utf-8 -*-

from panda_script_functions import *

import getpass

from pandas import * # how does this differ from next line?

import pandas

import numpy as np

import matplotlib

import matplotlib.pyplot as plt

x = pandas.__version__

print(x)

plot arange(10)

%pylab inline

def side_by_side(*objs, **kwds):

print adjoin(space, *reprs)

plt.rc('figure', figsize=(10, 6))

# adjoin ?

# Panda series and dataframe

# R dataframe is consistent concept here.

# Index = label array

# Descriptive stats

# Doing group ops on data that easily can be grouped

# Aggregations or transformations like subtracting mean value - using group by...

# Pivot tables

# Summary of data sets.

# Merge data sets. JOIN-like.

# Time-series

# baby-names.csv = top 1000 names for both boys and girls over the years....

# record count = 2000 records per year *

# json database from usda

# json to csv => descriptive stats

# heapy and timeit

#