Charles Kelly explains how to merge, copy, and append Pandas DataFrame objects.
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- Exercise Files
- [Instructor] The merge file from your exercises…files folder is prepopulated with import statements…for pandas and num pi.…It contains two num pi data sets,…a date time index, and two sample data frames.…It also initializes a variable named…starting date to July 1, 2016.…Begin by placing your cursor in the import cell,…execute it by pressing shift+enter.…In order to examine pandas cancatination capabilities…we split sample data 2 into a list…that contains three elements.…
Execute this cell to see the results…that appear in the variable pieces.…Next we'll use this nude list as an argument…to the cancat function that produces a new data frame.…Look at the fruits column.…You'll see that banana and strawberry…are not contained in this new data frame.…The documentation for panda's append function…tells us that the function append row of the other,…which is the first parameter to the end of the data frame…to which it is applied then returns a new object.…
Columns not in this frame are added as new columns.…We'll use the iLoc or the iLocation function…
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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