Exploratory Data Analysis With Python and Pandas

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在此指導項目中,您將:

Apply practical Exploratory Data Analysis (EDA) techniques on any tabular dataset using Python packages such as Pandas and Numpy.

Produce data visualizations using Seaborn and Matplotlib

Clock2 hours
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

In this 2-hour long project-based course, you will learn how to perform Exploratory Data Analysis (EDA) in Python. You will use external Python packages such as Pandas, Numpy, Matplotlib, Seaborn etc. to conduct univariate analysis, bivariate analysis, correlation analysis and identify and handle duplicate/missing data. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

您要培養的技能

Python ProgrammingData AnalysisPandasExploratory Data AnalysisEDA

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Initial Data Exploration: Read in data, take a glimpse at a few rows, calculate some summary statistics.

  2. Univariate Analysis: Analyze continuous and categorical variables, one variable at a time.

  3. Bivariate Analysis: Looking at the relationship between two variables at a time.

  4. Identify and Handling Duplicate and Missing Data: Find and remove duplicate rows, and replace missing values with their mean and mode.

  5. Correlation Analysis: Looking at the correlation of numerical variables in the dataset and interpreting the numbers.

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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