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Pandas 1.x Cookbook - Second Edition

You're reading from  Pandas 1.x Cookbook - Second Edition

Product type Book
Published in Feb 2020
Publisher Packt
ISBN-13 9781839213106
Pages 626 pages
Edition 2nd Edition
Languages
Authors (2):
Matt Harrison Matt Harrison
Profile icon Matt Harrison
Theodore Petrou Theodore Petrou
Profile icon Theodore Petrou
View More author details

Table of Contents (17) Chapters

Preface Pandas Foundations Essential DataFrame Operations Creating and Persisting DataFrames Beginning Data Analysis Exploratory Data Analysis Selecting Subsets of Data Filtering Rows Index Alignment Grouping for Aggregation, Filtration, and Transformation Restructuring Data into a Tidy Form Combining Pandas Objects Time Series Analysis Visualization with Matplotlib, Pandas, and Seaborn Debugging and Testing Pandas Other Books You May Enjoy
Index

Series operations

There exist a vast number of operators in Python for manipulating objects. For instance, when the plus operator is placed between two integers, Python will add them together:

>>> 5 + 9  # plus operator example. Adds 5 and 9
14

Series and DataFrames support many of the Python operators. Typically, a new Series or DataFrame is returned when using an operator.

In this recipe, a variety of operators will be applied to different Series objects to produce a new Series with completely different values.

How to do it…

  1. Select the imdb_score column as a Series:
    >>> movies = pd.read_csv("data/movie.csv")
    >>> imdb_score = movies["imdb_score"]
    >>> imdb_score
    0       7.9
    1       7.1
    2       6.8
    3       8.5
    4       7.1
           ... 
    4911    7.7
    4912    7.5
    4913    6.3
    4914    6.3
    4915    6.6
    Name: imdb_score, Length: 4916, dtype: float64
    
  2. Use the plus operator...
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