Conducting Exploratory Data Analysis
Conduct exploratory data analysis with a systematic approach to investigate different aspects of your data: comparisons, relationships, compositions, and distributions. This guided project gives you a framework so you can conduct your own exploratory data analysis and make your work more professional and organized. The language is Python and the libraries used are seaborn, pandas, and matplotlib.
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- Level Intermediate
- Duration 3 hours
- Course by Coursera Project Network
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Conduct exploratory data analysis with a systematic approach to investigate different aspects of your data: comparisons, relationships, compositions, and distributions. This guided project gives you a framework so you can conduct your own exploratory data analysis and make your work more professional and organized. The language is Python and the libraries used are seaborn, pandas, and matplotlib.Modules
Your Learning Journey
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Assignment
- Assess Your Knowledge
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Labs
- Conducting Exploratory Data Analysis
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Readings
- Project Overview
- Takeaway Document - Conducting Exploratory Data Analysis
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Unlock the power of data with "Conducting Exploratory Data Analysis" by Coursera. This intermediate-level course delves into systematic methods for investigating data comparisons, relationships, compositions, and distributions using Python. Over 180 minutes, master libraries like seaborn, pandas, and matplotlib. Ideal for data science enthusiasts, this free course ensures your analysis is professional and organized.
João Vitor Boverio da Silva Gomes