ExpiredPython Data Analytics: With Pandas and NumPy

Welcome to ” Python Data Analytics: With Pandas and NumPy ”

Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more!

You will learn how to:

• Import data sets
• Clean and prepare data for analysis
• Manipulate pandas DataFrame
• Summarize data
• Build machine learning models using scikit-learn
• Build data pipelines
• Posing a question
• Wrangling your data into a format you can use and fixing any problems with it
• Exploring the data, finding patterns in it, and building your intuition about it
• Drawing conclusions and/or making predictions
• Communicating your findings

Data Analysis with Python is delivered through lecture, hands-on labs, and assignments. It includes following parts:

• Data Analysis libraries: will learn to use Pandas DataFrames, Numpy multi-dimentional arrays, and SciPy libraries to work with a various datasets. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions

COURSE SYLLABUS

Module 1 – Installation

• Lecture 1: Installing the Anaconda Python distribution
• Lecture 2:Writing and running Python in the iPython notebook

Module 2 – Refresher Data Containers in Python

• Lecture 3:Python containers overview
• Lecture 4:Using Python lists and the slicing syntax
• Lecture 5:Using Python dictionaries
• Lecture 6:Comprehensive

Module – 3 Word Anagrams in Python

• Lecture 7:Word anagram overview
• Lecture 8:Loading the dictionary
• Lecture 9:Finding anagrams
• Lecture 10:Challenge
• Lecture 11:Solution

Module – 4 Introduction to NumPy

• Lecture 12:NumPy overview
• Lecture 13:Creating Numpy Arrays
• Lecture 14:Doing math with arrays
• Lecture 15:Indexing and slicing
• Lecture 16:Records and dates

Module – 5 Weather Data with NumPy

• Lecture 17:Weather data overview
• Lecture 18:Downloading and parsing data files
• Lecture 19:Temperature analysis
• Lecture 20:Integrating missing data
• Lecture 21:Smoothing data
• Lecture 22:Computing daily records
• Lecture 23:Challenge
• Lecture 24:weather data Solution

Module – 6 Introduction to Pandas

• Lecture 25:Pandas overview
• Lecture 26:Series in Pandas
• Lecture 27:DataFrames in Pandas
• Lecture 28:Using multilevel indices
• Lecture 29:Aggregation

You’ll also learn how to use the Python libraries NumPy, Pandas, and Matplotlib to write code that’s cleaner, more concise, and runs faster.

Take this course today and start your journey now!

Regards,

EliteHakcer Team