Chapter 4 - Practical Data Visualization
Segment 5 - Visualizing time series
import numpy as np
from numpy.random import randn
import pandas as pd
from pandas import Series, DataFrame
import matplotlib.pyplot as plt
from pylab import rcParams
%matplotlib inline
rcParams['figure.figsize'] = 5, 4
The simplest time series plot
address = '~/Data/Superstore-Sales.csv'
df = pd.read_csv(address, index_col='Order Date',encoding='cp1252', parse_dates=True)
df.head()
|
Row ID |
Order ID |
Order Priority |
Order Quantity |
Sales |
Discount |
Ship Mode |
Profit |
Unit Price |
Shipping Cost |
Customer Name |
Province |
Region |
Customer Segment |
Product Category |
Product Sub-Category |
Product Name |
Product Container |
Product Base Margin |
Ship Date |
| Order Date |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2010-10-13 |
1 |
3 |
Low |
6 |
261.5400 |
0.04 |
Regular Air |
-213.25 |
38.94 |
35.00 |
Muhammed MacIntyre |
Nunavut |
Nunavut |
Small Business |
Office Supplies |
Storage & Organization |
Eldon Base for stackable storage shelf, platinum |
Large Box |
0.80 |
10/20/2010 |
| 2012-10-01 |
49 |
293 |
High |
49 |
10123.0200 |
0.07 |
Delivery Truck |
457.81 |
208.16 |
68.02 |
Barry French |
Nunavut |
Nunavut |
Consumer |
Office Supplies |
Appliances |
1.7 Cubic Foot Compact "Cube" Office Refrigera... |
Jumbo Drum |
0.58 |
10/2/2012 |
| 2012-10-01 |
50 |
293 |
High |
27 |
244.5700 |
0.01 |
Regular Air |
46.71 |
8.69 |
2.99 |
Barry French |
Nunavut |
Nunavut |
Consumer |
Office Supplies |
Binders and Binder Accessories |
Cardinal Slant-D® Ring Binder, Heavy Gauge Vinyl |
Small Box |
0.39 |
10/3/2012 |
| 2011-07-10 |
80 |
483 |
High |
30 |
4965.7595 |
0.08 |
Regular Air |
1198.97 |
195.99 |
3.99 |
Clay Rozendal |
Nunavut |
Nunavut |
Corporate |
Technology |
Telephones and Communication |
R380 |
Small Box |
0.58 |
7/12/2011 |
| 2010-08-28 |
85 |
515 |
Not Specified |
19 |
394.2700 |
0.08 |
Regular Air |
30.94 |
21.78 |
5.94 |
Carlos Soltero |
Nunavut |
Nunavut |
Consumer |
Office Supplies |
Appliances |
Holmes HEPA Air Purifier |
Medium Box |
0.50 |
8/30/2010 |
df['Order Quantity'].plot()
<matplotlib.axes._subplots.AxesSubplot at 0x7eff835be588>
df2 = df.sample(n=100, random_state=25, axis=0)
plt.xlabel('Order Date')
plt.ylabel('Order Quantity')
plt.title('Superstore Sales')
df2['Order Quantity'].plot()
<matplotlib.axes._subplots.AxesSubplot at 0x7eff8145ce10>
Refer to: https://docs.python.org/2/library/datetime.html