Join Charles Kelly for an in-depth discussion in this video Operations, part of Pandas for Data Science.
- [Instructor] The operations file…from your exercises file folder…is prepopulated with import statements…for pandas and num pi.…It also contains a num pi data set,…a date time index and two sample data frames.…It initializes a variable named starting date…to July 1, 2016.…Begin by placing your cursor in the import cell…and execute the cell by pressing shift+enter.…Our first example of a built in operation…is panda's describe function.…
You can execute this cell again by pressing shift+enter.…By default the describe function returns…eight popular descriptive statistics.…You can see that I've used the display precision option…to set the display output to two positions…after the decimal point.…In our next operation we'll use the mean function…to calculate the means of each column of data…in our data set.…As you can see each column is listed…in the left hand column and the value…of the mean for each column is listed…in the right hand column.…
In contrast to the column's means,…you can obtain the row means by passing…
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
Introduction to Data Analysis with Pythonwith Michele Vallisneri2h 16m Intermediate
NumPy Data Science Essential Trainingwith Charles Kelly3h 54m Intermediate
SQL for Data Reporting and Analysiswith Emma Saunders2h 16m Intermediate
1. Introduction to Notebooks
2. Pandas Overview
4. Data Frames and Panels
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