Python Functions for Data Science
Offered By: LinkedIn Learning
Course Description
Overview
Save time, and make your code more readable and reusable, by learning the most powerful Python functions for data science.
Syllabus
Introduction
- Python functions you should know
- Getting the most from this course
- Python print() function
- Python input() function
- Python abs() function
- Python round() function
- Python min() function
- Python max() function
- Python sorted() function
- Python sum() function
- Python len() function
- Python type() function
- Python map() function
- Python zip() function
- Python filter() function
- Create NumPy arrays in Python
- Minimum and maximum values in NumPy arrays
- Indices of min and max values in NumPy arrays
- Find shapes of NumPy arrays and reshape
- Select items or groups of items from NumPy arrays
- Arithmetic operations on NumPy arrays
- Scalar operations on NumPy arrays
- Statistical operations on NumPy arrays
- Other operations on NumPy arrays
- Linear algebra operations with SciPy
- Statistical functions with SciPy
- Create a pandas series
- Create a pandas DataFrame
- Select data subsets from pandas objects
- Modify pandas objects
- Combine data from pandas objects
- Group data from pandas objects
- Matplotlib line plots
- Matplotlib scatter plots
- Matplotlib bar plots
- Matplotlib pie charts
- Matplotlib histograms
- Matplotlib subplots
- Seaborn box plots
- Seaborn kernel density estimate plots
- Seaborn violin plots
- Seaborn heatmaps
- Get started using Python functions
Taught by
Lavanya Vijayan and Madecraft
Related Courses
Inferential Statistical Analysis with PythonUniversity of Michigan via Coursera Data Analyst
Udacity Exploratory Data Analysis with Seaborn
Coursera Project Network via Coursera Analyze Box Office Data with Seaborn and Python
Coursera Project Network via Coursera Statistical Data Visualization with Seaborn
Coursera Project Network via Coursera