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You're reading fromPython Machine Learning (Wiley)

Product type Book
Published in Apr 2019
Publisher Wiley
ISBN-13 9781119545637
Pages 320 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Wei-Meng Lee

1. Cover
2. Introduction
3. CHAPTER 1: Introduction to Machine Learning 4. CHAPTER 2: Extending Python Using NumPy 5. CHAPTER 3: Manipulating Tabular Data Using Pandas 6. CHAPTER 4: Data Visualization Using matplotlib 7. CHAPTER 5: Getting Started with Scikit‐learn for Machine Learning 8. CHAPTER 6: Supervised Learning—Linear Regression 9. CHAPTER 7: Supervised Learning—Classification Using Logistic Regression 10. CHAPTER 8: Supervised Learning—Classification Using Support Vector Machines 11. CHAPTER 9: Supervised Learning—Classification Using K‐Nearest Neighbors (KNN) 12. CHAPTER 10: Unsupervised Learning—Clustering Using K‐Means 13. CHAPTER 11: Using Azure Machine Learning Studio 14. CHAPTER 12: Deploying Machine Learning Models 15. Index

Pandas Series

A Pandas Series is a one‐dimensional NumPy‐like array, with each element having an index (0, 1, 2, … by default); a Series behaves very much like a dictionary that includes an index. Figure 3.1 shows the structure of a Series in Pandas.

To create a Series, you first need to import the `pandas` library (the convention is to use `pd` as the alias) and then use the `Series` class:

````import pandas as pd`
`series = pd.Series([1,2,3,4,5])`
`print(series)` ```

The preceding code snippet will print the following output:

````0    1`
`1    2`
`2    3`
`3    4`
`4    5`
`dtype: int64` ```

By default, the index of a Series starts from 0.

Creating a Series Using a Specified Index

You can specify an optional index for a Series using the `index` parameter:

````series = pd.Series([1,2,3,4,5], index=['a','b','c','d','c'])`
`print(series)` ```

The preceding code snippet prints out the following:

````a    1`
`b    2`
`c    3`
`d    4`
`c    5`
`dtype...````
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