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Pandas 1.x Cookbook

You're reading from   Pandas 1.x Cookbook Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781839213106
Length 626 pages
Edition 2nd Edition
Languages
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Authors (2):
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Theodore Petrou Theodore Petrou
Author Profile Icon Theodore Petrou
Theodore Petrou
Matthew Harrison Matthew Harrison
Author Profile Icon Matthew Harrison
Matthew Harrison
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Table of Contents (17) Chapters Close

Preface 1. Pandas Foundations 2. Essential DataFrame Operations FREE CHAPTER 3. Creating and Persisting DataFrames 4. Beginning Data Analysis 5. Exploratory Data Analysis 6. Selecting Subsets of Data 7. Filtering Rows 8. Index Alignment 9. Grouping for Aggregation, Filtration, and Transformation 10. Restructuring Data into a Tidy Form 11. Combining Pandas Objects 12. Time Series Analysis 13. Visualization with Matplotlib, Pandas, and Seaborn 14. Debugging and Testing Pandas 15. Other Books You May Enjoy
16. Index

Selecting a column

Selected a single column from a DataFrame returns a Series (that has the same index as the DataFrame). It is a single dimension of data, composed of just an index and the data. You can also create a Series by itself without a DataFrame, but it is more common to pull them off of a DataFrame.

This recipe examines two different syntaxes to select a single column of data, a Series. One syntax uses the index operator and the other uses attribute access (or dot notation).

How to do it…

  1. Pass a column name as a string to the indexing operator to select a Series of data:
    >>> movies = pd.read_csv("data/movie.csv")
    >>> movies["director_name"]
    0           James Cameron
    1          Gore Verbinski
    2              Sam Mendes
    3       Christopher Nolan
    4             Doug Walker
                  ...        
    4911          Scott Smith
    4912                  NaN
    4913     Benjamin Roberds
    4914          Daniel...
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