3.75 (58 reviews)
☑ How-to install Python and Anaconda - the worlds largest Data Science platform.
☑ How-to create a virtual environment using Conda.
☑ How-to setup the Atom Text Editor.
☑ How to clone a GitHub Repository in Atom Text Editor.
☑ How-to create a new branch in Atom Text Editor.
☑ Use Python Pandas to read in large data-sets such as stock price information, customer information, purchase information and more.
☑ Use Pandas DataFrames to work with tabular data.
☑ Inspect datasets to gain quick valuable insights.
☑ Use conditional filtering to select relevant information from datasets.
☑ Using NumPy and Pandas together.
☑ Create Pandas DataFrames from scratch.
☑ Create DataFrames from Python dictionaries.
☑ Using Broadcasting with DataFrames.
☑ Correctly labeling data and columns.
☑ Data cleansing techniques.
☑ Using Python Pandas to create graphical plots such as bar, line, area, scatter etc.
☑ How-to analysis datasets using statistical methods such as min, mas, mean, std.
☑ Create filters in your code to extract targeted data from large datasets.
☑ How-to manage time data in Python with Pandas.
☑ Correctly index time data and create DateTime indexes.
☑ Partial String Indexing and slicing.
☑ Resampling Pandas Time Data.
☑ Method Chaining.
☑ Separating and Resampling.
Python Pandas are one of the most used libraries in Python when it comes to data analysis and manipulation. Whether in finance, scientific fields, or data science, a familiarity with Pandas is a must have. This course teaches you how to work with real-world data sets for analyzing data in Python using Pandas. Not only will you learn how to manipulate and analyse data you will also learn powerful and easy to use visualization techniques for representing your data.
This course kicks off by showing you how to get up and running using GitHub, an essential skill in your coding career. Ideally, to get the best from this course you should have some Python programming experience.
Every piece of code and dataset used in this course is available to download for free from GitHub.
Without doubt this course will teach you the necessary skills to apply basic data science techniques which are use the world over by experienced data scientists and those who spend their working day in spreadsheets.
How to access course source code
Setting up Python, Anaconda, Atom and GitHub
Setting up Python with Anaconda
Setting up Atom Text Editor
Creating Virtual Environments
How to clone a GitHub Repository
Introduction to Python Pandas
Introduction to Pandas
Introduction to DataFrames
Using NumPy and Pandas Together
Creating DataFrames from NumPy
Creating DataFrames from Dictionaries
Using Broadcasting in Pandas
Labeling data in a DataFrame
Building DataFrames with Broadcasting
Cleansing, Importing and Exporting Data
Creating Plots with Pandas
Visual Data Analysis
Creating Graphs with Pandas Plot Lines
Creating Graphs with Pandas Scatter Plots
Creating Graphs with Pandas Bar Plots
Statistical Exploratory Data Analysis
Managing Dates and Times with Python Pandas
Introduction to Pandas DateTime
Indexing Pandas Time Series
Creating and using a DateTimeIndex
Resampling Pandas Time Data
Separating and Resampling
Additional Filtering Methods
Visualizing Pandas Time Data
APPENDIX A: How to use the Atom Text Editor to push code to GitHub
The course is descriptive enough to learn the basics of Pandas, which the course covers as expected. Thank you Tony.