March 2020
Beginner to intermediate
352 pages
8h 40m
English
Content preview from Hands-On Exploratory Data Analysis with Python
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EDA on Wine Quality Data Analysis
We have discussed a plethora of tools and techniques regarding Exploratory Data Analysis (EDA) so far, including how we can import datasets from different sources and how to remove outliers from the dataset, perform data analysis on the dataset, and generate illustrative visualization from such a dataset. In addition to this, we have discussed how we can apply advanced data analysis such as the correlation between variables, regression analysis, and time series analysis, and build advanced models based on such datasets. In this chapter, we are going to apply all of these techniques to the Wine Quality dataset.
The main topics discussed in this chapter include the following:
- Disclosing the wine quality dataset ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.