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By the end of this course you will know how to: Use Anaconda, the worlds leading data science platform, to setup Python and manage libraries. Install and setup the free to use Atom Text Editor. Create Virtual Environments. Clone a GitHub Repository directly into Atom. Create new code branches in GitHub and Atom. Install the Pandas library.
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dframe Output: Importing Data with Pandas The first step is to read the data. The data is stored as a comma-separated values, or csv, file, where each row is separated by a new line, and each column by a comma (,). In order to be able to work with the data in Python, it is needed to read the csv file into a Pandas DataFrame.
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2024 Python Data Analysis & Visualization Masterclass Pandas, Matplotlib, Seaborn, & More! Analyze Dozens of Datasets & Create Stunning Visualizations Highest rated 4.7 (2,224 ratings) 18,964 students Created by Colt Steele Last updated 4/2023 English English [Auto], Simplified Chinese [Auto] 2024 Python Data Analysis & Visualization Masterclass
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In this article, we'll embark on a journey to master data visualization in Python, exploring key libraries and techniques to transform raw data into insightful visuals. To enhance our learning, we'll utilize a basic example dataset, providing hands-on code examples using Matplotlib, Seaborn, and Plotly.