Exploratory Data Analysis With Python and Pandas

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Coursera Project Network
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En este proyecto guiado, tú:

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
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

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.

Habilidades que desarrollarás

Python ProgrammingData AnalysisPandasExploratory Data AnalysisEDA

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  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.

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso




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