Charles Kelly explains how to use NumPy universal function within the context of Pandas data frames.
- [Narrator] If the data within a DataFrame are numeric,…NumPy's Universal functions can be used…on or with the DataFrame.…You should note that this is slightly different…that the approach that we took with Series,…where we used Series Apply function…to use Universal functions.…The Universal file in your exercise's file folder…is prepopulated with import statements for Pandas and NumPy,…as well as sample DataFrames.…Place your cursor in the import cell and press shift enter…to execute the cell.…
Do the same thing for the DataFrame cell.…In this cell, the plus symbol is actually overloaded…as an element by element or a vectorized Universal function.…For creating the sums of separate DataFrames.…Here we see the result as the sum DataFrame.…Here we use NumPy's exponential operator.…That is, the value of E or the basis of the natural number,…oiler's number, is exponentiated to a value in its argument.…
Note that when we look at the results for this,…not a number is handled correctly within the NumPy function.…In this example, we illustrate that a Transpose…
Watch this course to gain an overview of Pandas. Charles Kelly helps you get started with time series, data frames, panels, plotting, and visualization. All you need is a copy of the free and interactive Jupyter Notebook app to practice and follow along.
- Using the Markdown language and Jupyter Notebook
- Creating objects
- Selecting objects
- Using operations
- Merging data
- Creating series
- Creating data frames
- Creating panels
- Annotating plots and data frame plots
Skill Level Intermediate
NumPy Data Science Essential Trainingwith Charles Kelly3h 54m Intermediate
SQL: Data Reporting and Analysiswith Emma Saunders2h 16m Intermediate
1. Introduction to Notebooks
2. Pandas Overview
4. Data Frames and Panels
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