Charles Kelly explains input and output operations within Pandas.
- [Instructor] The input and output file from your…Exercises files folder, is pre-populated…with imports statements for Pandas and NumPy.…It also includes statements that read data…from a Microsoft Excel file and write data…to a Comma-Separated Values file.…Begin by placing your cursor in this cell,…and execute it by pressing Shift, Enter.…Next, go to the cell that starts with file_name_string.…You'll need to adjust this string so that it points…to the location where you installed…your Exercise files on your computer.…
If you haven't installed the Exercise files,…I'll show you how to create an Excel file…that has similar data.…This is the EmployeesWithGrades Excel file…that is included with your Exercises file folder.…If you'd like to create an example on your own,…create data that is similar to this data.…If you have an Excel file available,…you'll need several arguments…to pastor the pd.read_excel function.…Notice it's pd, not Pandas because of our name space change?…The first parameter is a filename string.…
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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