What is Pandas? - Deepstash
Machine Learning With Google

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How Google uses logic in machine learning

Machine Learning With Google

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What is Pandas?

Python Data Analysis Library, called Pandas, is a Python library built for data analysis and manipulation. It’s open-source and supported by Anaconda. It is particularly well suited for structured (tabular) data.

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Where do I start?

  • QL is a declarative programming language.
  • With SQL, you declare what you want in a sentence that almost reads like English.
  • Pandas’ syntax is quite different from SQL. In Pandas, you apply operations on the dataset, and chain...

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The anatomy of a SQL query

A SQL query consists of a few important keywords. Between those keywords, you add the specifics of what data, exactly, you want to see. Here is a skeleton query without the specifics:

SELECT… FROM… WHERE…

GROUP BY… HAVING…

ORDER BY…

LIMIT… OFFSET…

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SQL

SQL was a go-to tool when you needed to get a quick-and-dirty look at some data, and draw preliminary conclusions that might, eventually, lead to a report or an application being written. This is called exploratory analysis.

These days, data comes in many shapes and forms, ...

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Other key differences

Data collection

  • Python supports all kinds of data formats.
  • R is designed for data analysts to import data from Excel, CSV and text files.

Data exploration

  • In Python, you ...

Python data processing with pandas

Pandas is a Python language package, which is used for data processing. This is a very common basic programming library when we use Python language for machine learning programming. This article is an introductory tutorial to it. Pandas provide fast, flexible and expressive data structures with t...

The main difference between R and Python

They approach data science differently:

  • R is used for statistical analysis.
  • Python provides a more general approach to data.
  • R is built by statisticians and leans heavily into statistical model...

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