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Published inJun 2022
PublisherPackt
ISBN-139781801075541
Edition1st Edition
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Tarek A. Atwan
Tarek A. Atwan
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Tarek A. Atwan

Tarek A. Atwan is a data analytics expert with over 16 years of international consulting experience, providing subject matter expertise in data science, machine learning operations, data engineering, and business intelligence. He has taught multiple hands-on coding boot camps, courses, and workshops on various topics, including data science, data visualization, Python programming, time series forecasting, and blockchain at various universities in the United States. He is regarded as a data science mentor and advisor, working with executive leaders in numerous industries to solve complex problems using a data-driven approach.
Read more about Tarek A. Atwan

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Handling missing data with interpolation

Another commonly used technique for imputing missing values is interpolation. The pandas library provides the DataFrame.interpolate() method for more complex univariate imputation strategies.

For example, one of the interpolation methods available is linear interpolation. Linear interpolation can be used to impute missing data by drawing a straight line between the two points surrounding the missing value (in time series, this means for a missing data point, it looks at a prior past value and the next future value to draw a line between them). A polynomial interpolation, on the other hand, will attempt to draw a curved line between the two points. Hence, each method will have a different mathematical operation to determine how to fill in for the missing data.

The interpolation capabilities in pandas can be extended further through the SciPy library, which offers additional univariate and multivariate interpolations.

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Time Series Analysis with Python Cookbook
Published in: Jun 2022Publisher: PacktISBN-13: 9781801075541
© 2022 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Tarek A. Atwan

Tarek A. Atwan is a data analytics expert with over 16 years of international consulting experience, providing subject matter expertise in data science, machine learning operations, data engineering, and business intelligence. He has taught multiple hands-on coding boot camps, courses, and workshops on various topics, including data science, data visualization, Python programming, time series forecasting, and blockchain at various universities in the United States. He is regarded as a data science mentor and advisor, working with executive leaders in numerous industries to solve complex problems using a data-driven approach.
Read more about Tarek A. Atwan

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