Oil Price Data with Python

This example shows how Python can be used to take a look at oil prices. The script gathers daily oil price data from Quandl and plots how the price has changed over the past few months.

Gathering data

First, we import pandas, numpy, and matplotlib and give them conventional short names.

In [1]:

# Import libraries
import pandas as pd
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
%matplotlib inline

Next, we identify the url for our data. In this case, the data is provided by Quandl and the url can be obtained by clicking ‘csv’ under the API for any series on the right-hand side of the page. We read the CHRIS CME_CL1 csv file provided by Quandl into a pandas dataframe.

In [2]:

# Import from Quandl WTI crude oil price data
url = "https://www.quandl.com/api/v3/datasets/CHRIS/CME_CL1.csv"
wticl1 = pd.read_csv(url, index_col=0, parse_dates=True)
wticl1.sort_index(inplace=True)
wticl1_last = wticl1['Last']
wticl1['PctCh'] = wticl1.Last.pct_change()

Line plot of oil price

Lastly, we can use matplotlib to generate a line plot showing the most recent 68 days worth of closing prices for WTI crude front month contracts. The past week has seen this measure of oil prices reach nearly $40 per barrel.

In [3]:

fig = plt.figure(figsize=[7,5])
ax1 = plt.subplot(111)
line = wticl1_last.tail(68).plot(color='red',linewidth=3)
ax1.set_ylabel('USD per barrel')
ax1.set_xlabel('')
ax1.set_title('WTI Crude Oil Price', fontsize=18)
ax1.spines["top"].set_visible(False)  
ax1.spines["right"].set_visible(False)  
ax1.get_xaxis().tick_bottom()
ax1.get_yaxis().tick_left()
ax1.tick_params(axis='x', which='major', labelsize=8)
fig.text(0.15, 0.85,'Last: $' + str(wticl1.Last[-1])\
         + ' (as of: ' \
         + str(wticl1.index[-1].strftime('%Y-%m-%d'))\
         + ')');
fig.text(0.15, 0.80,'Change: $' + str(wticl1.Change[-1])\
         + '; ' \
         + str((np.round((wticl1.PctCh[-1] * 100), \
         decimals=2))) + '%')
fig.text(0.1, 0.06, 'Source: ' + url)
fig.text(0.1, 0.02, 'briandew.wordpress.com')
plt.savefig('oil.png', dpi=1000)