Learn how to group and aggregate data.
- [Instructor] Now we're going to talk about…data grouping and aggregation.…Grouping and aggregation are useful for exploring…and describing your dataset and its subgroups.…Imagine you're a merchant that sells fruit…and you have a dataset…that describes the different types of fruit you have…and where you purchased them from.…To understand what a subgroup is,…look at this example of the dataset…that has apple and orange records.…If you were to reduce this dataset down…to its fundamental subgroups by fruit category,…you would get two records, apple and orange.…
Grouping is an excellent method to use…when you want to explore and understand your data…and its inherent subgroups.…It's useful for many, many reasons.…You can group data in order to compare subsets…and deduce reasons why subgroups differ the way they do…or you may only be interested in specific subgroups…for your analysis.…Grouping can help you identify…and subset out those subgroups.…So let's look at how data aggregation…and grouping work in practice.…For this demonstration,…
AuthorLillian Pierson, P.E.
- Getting started with Jupyter Notebooks
- Visualizing data: basic charts, time series, and statistical plots
- Preparing for analysis: treating missing values and data transformation
- Data analysis basics: arithmetic, summary statistics, and correlation analysis
- Outlier analysis: univariate, multivariate, and linear projection methods
- Introduction to machine learning
- Basic machine learning methods: linear and logistic regression, Naïve Bayes
- Reducing dataset dimensionality with PCA
- Clustering and classification: k-means, hierarchical, and k-NN
- Simulating a social network with NetworkX
- Creating Plot.ly charts
- Scraping the web with Beautiful Soup
Skill Level Beginner
1. Data Munging Basics
2. Data Visualization Basics
3. Basic Math and Statistics
4. Dimensionality Reduction
Explanatory factor analysis6m 39s
5. Outlier Analysis
6. Cluster Analysis
7. Network Analysis with NetworkX
8. Basic Algorithmic Learning
9. Web-based Data Visualizations with Plotly
10. Web Scraping with Beautiful Soup
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.