import pandas as pd
data = pd.read_csv('../data/examp-data.txt')
print(data)

data_w_index = pd.read_csv('../data/examp-data.txt', index_col=0)
print(data_w_index)

data.to_csv('../data/pandas_output.csv')
!cat ./data/pandas_output.csv

data.to_csv('../data/pandas_output.csv', index=False)
!cat ./data/pandas_output.csv

data['y']

data[['z', 'x']]

data_w_index

data_w_index.loc[2]

data_w_index.iloc[0]

data.iloc[0]

data_w_index[0:2]

for row in data.values:
    print row * 2

data.values[0]
data.ix[1]

data[data['y'] > 2.0]

data[(data['x'] > 1) & (data['y'] > 2)]

data['y'] * data['z'] + 2

import numpy as np
np.log(data['y']) * np.sqrt(data['z'])

url = "http://esapubs.org/archive/ecol/E084/093/Mammal_lifehistories_v2.txt"
data = pd.read_csv(url, delimiter="\t")
data.head()

data_by_order = data.groupby('order')
for order, order_data in data_by_order:
    avg_mass = np.mean(order_data['mass(g)'])
    print "The average mass of {} is {} grams".format(order, avg_mass)