Python - Data Science | Common Functions for Exploratory Data Analysis
In this tutorial, we will learn "Common Functions for Exploratory Data Analysis" in our Data Science processes by using Python.
As we know Exploratory Data Analysis (EDA) is one of the most essential part of your data science process.
Python is one of the fastest growing programming languages.
1. Whether it’s data manipulation with Pandas,
2. Creating visualizations with Seaborn, or
3. Deep learning with TensorFlow,
Python seems to have a tool for everything.
Pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python.
NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
In the Data Science, in the most cases is not to explore the data but it is something about to analyze the data in some way, often through a model.
To learn more, please follow us -
http://www.sql-datatools.com
To Learn more, please visit our YouTube channel at -
/ sql-datatools
To Learn more, please visit our Instagram account at -
/ asp.mukesh
To Learn more, please visit our twitter account at -
/ macxima
Auf dieser Seite können Sie das Online-Video Python - Data Science | Common Functions for Exploratory Data Analysis mit der Dauer stunde minuten sekunde in guter Qualität ansehen, das der Benutzer Mukesh Singh 01 Januar 1970 hochgeladen hat, den Link mit Freunden und Bekannten teilen, dieses Video wurde auf Youtube bereits 251 Mal angesehen und es wurde von 1 den Zuschauern gefallen. Viel Spaß beim Betrachtenden Zuschauern gefallen!
