Differential D7384 Diff 35198 examples/airline_demo/airline_demo/notebooks/Fares_vs_Delays.ipynb

Changeset View

Standalone View

View Options

examples/airline_demo/airline_demo/notebooks/Fares_vs_Delays.ipynb

This file was deleted.

In [1]:

import dagstermill

In [2]:

from dagster import ModeDefinition, ResourceDefinition

from collections import namedtuple

url = 'postgresql://{username}:{password}@{hostname}:5432/{db_name}'.format(

username='test', password='test', hostname='localhost', db_name='test'

)

DbInfo = namedtuple('DbInfo', 'url')

context = dagstermill.get_context(

mode_def=ModeDefinition(

resource_defs={'db_info': ResourceDefinition(lambda _: DbInfo(url))}

)

table_name = 'delays_vs_fares'

db_url = context.resources.db_info.url

In [3]:

import os

import sqlalchemy as sa

import matplotlib.pyplot as plt

import numpy as np

import pandas as pd

from dagster.utils import mkdir_p

In [4]:

engine = sa.create_engine(db_url)

/Users/max/.virtualenvs/dagster/lib/python3.6/site-packages/psycopg2/__init__.py:144: UserWarning: The psycopg2 wheel package will be renamed from release 2.8; in order to keep installing from binary please use "pip install psycopg2-binary" instead. For details see: <http://initd.org/psycopg/docs/install.html#binary-install-from-pypi>. """)

In [5]:

from matplotlib.backends.backend_pdf import PdfPages

plots_path = os.path.join(os.getcwd(), 'plots')

mkdir_p(plots_path)

pdf_path = os.path.join(plots_path, 'fares_vs_delays.pdf')

pp = PdfPages(pdf_path)

In [6]:

fares_vs_delays = pd.read_sql('select * from {table_name}'.format(table_name=table_name), engine)

In [7]:

fares_vs_delays.head()

<div> <style scoped> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style> <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>origin</th> <th>dest</th> <th>avg_fare</th> <th>avg_fare_per_mile</th> <th>avg_arrival_delay</th> <th>avg_departure_delay</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>SFO</td> <td>IND</td> <td>434.767524</td> <td>0.142556</td> <td>4.730924</td> <td>11.188755</td> </tr> <tr> <th>1</th> <td>SFO</td> <td>CVG</td> <td>489.184236</td> <td>0.146830</td> <td>-6.628049</td> <td>4.054545</td> </tr> <tr> <th>2</th> <td>SFO</td> <td>MSY</td> <td>498.145642</td> <td>0.152935</td> <td>-6.733871</td> <td>6.397590</td> </tr> <tr> <th>3</th> <td>SFO</td> <td>SEA</td> <td>368.674415</td> <td>0.237027</td> <td>13.233090</td> <td>12.270567</td> </tr> <tr> <th>4</th> <td>SFO</td> <td>OKC</td> <td>428.348442</td> <td>0.186265</td> <td>10.461538</td> <td>15.736264</td> </tr> </tbody> </table> </div>

In [8]:

fares_vs_delays['avg_arrival_delay'].describe()

count 84.000000 mean 7.319261 std 11.965286 min -19.000000 25% 2.347601 50% 7.380119 75% 11.461447 max 93.090909 Name: avg_arrival_delay, dtype: float64

In [9]:

plt.scatter(fares_vs_delays['avg_arrival_delay'], fares_vs_delays['avg_fare'])

try:

z = np.polyfit(fares_vs_delays['avg_arrival_delay'], fares_vs_delays['avg_fare'], 1)

f = np.poly1d(z)

x_fit = np.linspace(fares_vs_delays['avg_arrival_delay'].min(), fares_vs_delays['avg_arrival_delay'].max(), 50)

y_fit = f(x_fit)

plt.plot(x_fit, y_fit, 'k--', alpha=0.5)

except:

pass

plt.title('Arrival Delays vs. Fares (Origin SFO)')

plt.xlabel('Average Delay at Arrival (Minutes)')

plt.ylabel('Average Fare ($)')

pp.savefig()

In [10]:

fig, ax = plt.subplots(figsize=(10,10))

for i, _ in enumerate(fares_vs_delays.index):

plt.text(

fares_vs_delays['avg_arrival_delay'][i],

fares_vs_delays['avg_fare_per_mile'][i],

fares_vs_delays['dest'][i],

fontsize=8)

plt.scatter(fares_vs_delays['avg_arrival_delay'], fares_vs_delays['avg_fare_per_mile'], alpha=0)

plt.title('Flight Delays (Origin SFO)')

plt.xlabel('Average Delay at Arrival (Minutes)')

plt.ylabel('Average Fare per Mile Flown($)')

pp.savefig()

In [11]:

pp.close()

In [2]:

from dagster import LocalFileHandle

dagstermill.yield_result(LocalFileHandle(pdf_path))