Learn how to concatenate and transform data.
- [Instructor] Knowing how to concatenate…and transform data is really important in data analysis.…Concatenation and data transformation…are useful for getting your data…into the structure and order you need for analysis.…For example, imagine you're mailing out…a piece of direct mail advertisement.…You have one table with customer ID and name,…and you have another table with customer ID,…mailing address, and age.…You mailing address application requires you to supply it,…one table that contains only customer name and address.…You generate this table by concatenating your two tables…by customer ID row wise.…
Concatenating is simply combining data…from separate sources.…Transformation, on the other hand,…is converting and reformatting data…to the format necessary for your purposes.…When you transform data,…you convert it into the format…that's required to facilitate analysis.…In this demonstration,…you're going to learn how to drop data,…add data, and sort data.…Going back to our example,…transformation would be when you drop the age column…
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
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