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Python Data Analysis

Python Data Analysis

By : Ivan Idris
3.9 (16)
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Python Data Analysis

Python Data Analysis

3.9 (16)
By: Ivan Idris

Overview of this book

This book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods using Python and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.
Table of Contents (22 chapters)
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Python Data Analysis
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Key Concepts
Online Resources
Index

Accessing databases from pandas


We can give pandas a database connection such as the one in the previous example or a SQLAlchemy connection. We will cover the latter in the later sections of this chapter. We will load the statsmodels sunactivity data, just like in the previous chapter, Chapter 7, Signal Processing and Time Series:

  1. Create a list of tuples to form the pandas DataFrame:

    rows = [tuple(x) for x in df.values]

    Contrary to the previous example, create a table without specifying data types:

    con.execute("CREATE TABLE sunspots(year, sunactivity)")
  2. The executemany() method executes multiple statements; in this case, we will be inserting records from a list of tuples. Insert all the rows into the table and show the row count as follows:

    con.executemany("INSERT INTO sunspots(year, sunactivity) VALUES (?, ?)", rows)
    c.execute("SELECT COUNT(*) FROM sunspots")
    print c.fetchone()

    The number of rows in the table is printed as follows:

    (309,)
    
  3. The rowcount attribute of the result of an execute() call...

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