Python Data Analysis with Pandas in 10 Minutes | Udemy Instructor, Frank Kane
In this video, Python Data Analysis with Pandas in 10 Minutes by Udemy Instructor, Frank Kane, you'll dive into the world of data science and machine learning in Python and learn the Pandas library.
Explore Frank Kane's full course on Udemy (special discount included in the link): https://bit.ly/2rbjcPl
Diving into the world of data science and machine learning in Python means learning the Pandas library – Pandas is everywhere in data science, and it is used to load, clean, and analyze your data before you pass it into other algorithms to extract meaning from it, or to conduct machine learning on it.
In just ten minutes, we’ll go through some examples of using Pandas on data in a real Python Jupyter Notebook. Pandas has its own syntax for manipulating and slicing arrays of data, and it is best learned by just seeing it in action.
In addition to Pandas, you'll see how Pandas interacts with NumPy and scikit_learn (sklearn,) to create complete data science workflows.
In this video, we will cover:
• Pandas Data Frames and Series, and how they slice and dice rows and columns of information
• Loading CSV data into Pandas
• Visualizing Pandas dataframes
• Working with dataframe dimensions
• Naming dataframe columns
• Extracting rows and columns from a dataframe
• Extracting single elements from a dataframe
• Sorting dataframes
• Aggregating dataframe data
• Plotting dataframes on graphs with matplotlib
If you have your own Python notebook environment, you can try your hand at a hands-on exercise at the end to load your own dataframe, extract relevant information from it, and plot a histogram from the remaining data.
You can’t be a data scientist without knowing Pandas! If you’re getting started in data science, this video is a must.
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