December 2018
Beginner to intermediate
490 pages
10h 38m
English
Content preview from Data Analysis with PythonBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Statistical exploration of time series
For the sample application, we'll use stock historical financial data provided by the Quandl data platform financial APIs (https://www.quandl.com/tools/api) and the quandl Python library (https://www.quandl.com/tools/python).
To get started, we need to install the quandl library by running the following command in its own cell:
!pip install quandl
Note
Note: As always, don't forget to restart the kernel after the installation is complete.
Access to the Quandl data is free but limited to 50 calls a day, but you can bypass this limit by creating a free account and get an API key:
- Go to https://www.quandl.com and create a new account by clicking on the SIGN UP button on the top right.
- Fill up the form in three steps ...
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