Learn how to perform arithmetic operations on data.
- [Instructor] The benefit of NumPy is it makes it…really easy to do math on data that's stored…in arrays and matrices.…I know we've talked a lot about arrays…and matrices in this course already, but just…to give you a formal definition.…An array is a one-dimensional container for elements…that are all of the same data type.…In contrast, matrix is a two-dimensional container…for elements that are stored in an array.…Let me give you an example of where NumPy can come in handy.…Have you ever tried to use a spreadsheet application…to perform mathematical operations on a data set…that has more than 300,000 rows?…What happened?…If the application didn't crash then it took…a lot of time and effort to get the program…to make the computation.…
With NumPy on the other hand you can quickly and easily…do mathematical and statistical operations on data sets…with even millions of records.…Simply put, NumPy makes it easy…to do math on large data sets.…Here are the arithmetic operators that you use in Python.…You use the same standard symbols…
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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