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Practical Time Series Analysis

You're reading from   Practical Time Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781788290227
Length 244 pages
Edition 1st Edition
Languages
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Authors (2):
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Avishek Pal Avishek Pal
Author Profile Icon Avishek Pal
Avishek Pal
PKS Prakash PKS Prakash
Author Profile Icon PKS Prakash
PKS Prakash
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Toc

Resampling time series data

The technique of resmapling is illustrated using a time series on chemical concentration readings taken every two hours between 1st January 1975 and 17th January 1975. The dataset has been downloaded from http://datamarket.com and is also available in the datasets folder of this book's GitHub repo.

We start by importing the packages required for running this example:

from __future__ import print_function 
import os 
import pandas as pd 
import numpy as np 
%matplotlib inline 
from matplotlib import pyplot as plt 

Then we set the working directory as follows:

os.chdir('D:/Practical Time Series') 

This is followed by reading the data from the CSV file in a pandas.DataFrame and displaying shape and the first 10 rows of the DataFrame:

df = pd.read_csv('datasets/chemical-concentration-readings.csv') 
print('Shape of the dataset...
You have been reading a chapter from
Practical Time Series Analysis
Published in: Sep 2017
Publisher: Packt
ISBN-13: 9781788290227
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