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Hands-On Data Analysis with Pandas

You're reading from   Hands-On Data Analysis with Pandas Efficiently perform data collection, wrangling, analysis, and visualization using Python

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Product type Paperback
Published in Jul 2019
Publisher
ISBN-13 9781789615326
Length 740 pages
Edition 1st 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. Introduction to Data Analysis FREE CHAPTER 3. Working with Pandas DataFrames 4. Section 2: Using Pandas for Data Analysis
5. Data Wrangling with Pandas 6. Aggregating Pandas DataFrames 7. Visualizing Data with Pandas and Matplotlib 8. Plotting with Seaborn and Customization Techniques 9. Section 3: Applications - Real-World Analyses Using Pandas
10. Financial Analysis - Bitcoin and the Stock Market 11. Rule-Based Anomaly Detection 12. Section 4: Introduction to Machine Learning with Scikit-Learn
13. Getting Started with Machine Learning in Python 14. Making Better Predictions - Optimizing Models 15. Machine Learning Anomaly Detection 16. Section 5: Additional Resources
17. 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.

CodeInText: 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 ...:

>>> import pandas as pd

>>> 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:
# handle the error here
pass

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.plot(
... x='date',
... y='price',
... kind='line',
... title='Price over Time',
... legend=False,
... 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
Warnings or important notes appear like this.
Tips and tricks appear like this.
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