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Learning pandas

You're reading from   Learning pandas High performance data manipulation and analysis using Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787123137
Length 446 pages
Edition 2nd Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (16) Chapters Close

Preface 1. pandas and Data Analysis FREE CHAPTER 2. Up and Running with pandas 3. Representing Univariate Data with the Series 4. Representing Tabular and Multivariate Data with the DataFrame 5. Manipulating DataFrame Structure 6. Indexing Data 7. Categorical Data 8. Numerical and Statistical Methods 9. Accessing Data 10. Tidying Up Your Data 11. Combining, Relating, and Reshaping Data 12. Data Aggregation 13. Time-Series Modelling 14. Visualization 15. Historical Stock Price Analysis

Appending new rows

Appending of rows is performed using the .append() method of the DataFrame. The process of appending returns a new DataFrame with the data from the original DataFrame added first and then rows from the second. Appending does not perform alignment and can result in duplicate index labels.

The following code demonstrates appending two DataFrame objects extracted from the sp500 data. The first DataFrame consists of rows (by position) 0, 1 and 2, and the second consists of rows (also by position) 10, 11 and 2. The row at position 2 (with label ABBV) is included in both to demonstrate the creation of duplicate index labels.

The set of columns of the DataFrame objects used in an append do not need to be the same. The resulting data frame will consist of the union of the columns in both, with missing column data filled with NaN. The following demonstrates this by...

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