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Predictive Data Analysis with Python

Series in Pandas

Explore the fundamentals of the Pandas Series object in Python, including how to create series with custom indexes, perform mathematical operations, and use functions to handle missing data. This lesson helps you build essential skills for managing and analyzing one-dimensional labeled data in predictive data analysis.

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Series #

Series can be described as a single column of a 2-D array or a matrix. It has specific index values attached to each row for identification. It can also be imagined as one column of an excel file.

The index values are automatically defined for each Series when it is created. These values can also be explicitly defined. Let’s look at an example to understand this:

Python 3.5
# importing pandas in our program
import pandas as pd
# Defining a series object
srs = pd.Series([1,2,3,4,5])
# printing series values
print("The Series values are:")
print(srs.values)
# printing series indexes
print("\nThe Index values are:")
print(srs.index.values)

The srs.values function on line 9 returns the values stored in the Series object and the function srs.index.values on line 13 returns the index values. ...