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Hands-On Data Analysis with Pandas

You're reading from   Hands-On Data Analysis with Pandas A Python data science handbook for data collection, wrangling, analysis, and visualization

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Product type Paperback
Published in Apr 2021
Publisher Packt
ISBN-13 9781800563452
Length 788 pages
Edition 2nd Edition
Languages
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Author (1):
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Stefanie Molin Stefanie Molin
Author Profile Icon Stefanie Molin
Stefanie Molin
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Toc

Table of Contents (21) Chapters Close

Preface 1. Section 1: Getting Started with Pandas
2. Chapter 1: Introduction to Data Analysis FREE CHAPTER 3. Chapter 2: Working with Pandas DataFrames 4. Section 2: Using Pandas for Data Analysis
5. Chapter 3: Data Wrangling with Pandas 6. Chapter 4: Aggregating Pandas DataFrames 7. Chapter 5: Visualizing Data with Pandas and Matplotlib 8. Chapter 6: Plotting with Seaborn and Customization Techniques 9. Section 3: Applications – Real-World Analyses Using Pandas
10. Chapter 7: Financial Analysis – Bitcoin and the Stock Market 11. Chapter 8: Rule-Based Anomaly Detection 12. Section 4: Introduction to Machine Learning with Scikit-Learn
13. Chapter 9: Getting Started with Machine Learning in Python 14. Chapter 10: Making Better Predictions – Optimizing Models 15. Chapter 11: Machine Learning Anomaly Detection 16. Section 5: Additional Resources
17. Chapter 12: The Road Ahead 18. Solutions
19. Other Books You May Enjoy Appendix

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, and user input. Here is an example: "Use pip to install the packages in the requirements.txt file."

A block of code is set as follows. The start of the line will be preceded by >>> and continuations of that line will be preceded by ...:

>>> df = pd.read_csv(
...     'data/fb_2018.csv', index_col='date', parse_dates=True
... )
>>> df.head()

Any code without the preceding >>> or ... is not something we will run—it is for reference:

try:
    del df['ones']
except KeyError:
    pass # handle the error here

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

>>> df.price.plot(
...     title='Price over Time', ylim=(0, None)
... )

Results will be shown without anything preceding the lines:

>>> pd.Series(np.random.rand(2), name='random')
0 0.235793
1 0.257935
Name: random, dtype: float64

Any command-line input or output is written as follows:

# Windows:
C:\path\of\your\choosing> mkdir pandas_exercises
# Linux, Mac, and shorthand:
$ mkdir pandas_exercises

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Using the File Browser pane, double-click on the ch_01 folder, which contains the Jupyter Notebook that we will use to validate our setup."

Tips or important notes

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