Exploratory Data Analysis in Python
|
Learn how to use exploratory data analysis (EDA) techniques in Python to evaluate, summarize, and visualize your data.
About this course
In this course, you will learn about exploratory data analysis techniques in Python, including:
EDA for data preparation
Summary statistics
Data visualization techniques
EDA prior to building a machine learning model
Prior to taking this course, you should have some knowledge of base Python and experience with pandas DataFrames.
Exploratory data analysis is an important part of any Data Scientist or Analyst’s workflow, so we highly recommend this course for anyone who is interested in working with data.
User Reviews
Be the first to review “Exploratory Data Analysis in Python”
Related Products
Discovering Predictive Analytics with Alteryx
Explore predictive analytics techniques and tools using Alteryx to forecast future trends based on historical data.
Real-Time Analytics with Apache Storm
Study the use of Apache Storm for processing real-time data streams and generating insights on-the-fly.
Analyze Data with R
Use R to process, analyze, and visualize data.
Predictive Analytics for Business
Learn to predict future outcomes and trends through statistical modeling techniques.
Introduction to Data Analysis with Pandas and NumPy
Learn to use Pandas and NumPy libraries for data manipulation and analysis in Python.
Firebase Analytics: iOS
Explore Firebase Analytics integration for iOS apps to analyze user behavior and app performance.
There are no reviews yet.