Mastering Data Analysis with Python Pandas

Description

In this course, you will :

• Python Pandas hands-on experience
• Learn about Python Pandas' data analysis and manipulation functions.
• After completing this course, you will be able to easily and efficiently perform data analysis and manipulation with Pandas.

Syllabus :

1. Pandas Data Structures

• Pandas Series
• Pandas DataFrame

 

2. Creating a Data Frame

• Reading Data from a File
• Create a DataFrame

 

3. Exploring a Data Frame

• Size of a DataFrame
• Data Types of Columns
• Different Values in a Column
• Measures of Central Tendency

 

4. Filtering a Data Frame

• Why Do We Need Filtering?
• Filtering with "loc" and "iloc" Methods
• Filtering by Selecting a Subset of Columns
• Filtering by Condition
• Filtering Rows with the Query Function

 

5. String Manipulation with Pandas

• Slicing and Indexing on Strings
• Splitting and Combining Strings
• Converting Strings to Upper and Lower Case
• Replacing Characters in a String
• Chained Operations

 

6. Date Manipulation with Pandas

• Pandas Date and Time Data Types
• Extracting Information from Dates
• The dt Accessor
• Manipulating Dates by Adding Time Intervals

 

7. Handling Missing Values with Pandas

• Missing Value Types and Representation
• Finding the Missing Values
• Dropping Rows and Columns with Missing Values
• Replacing the Missing Values

 

8. Data Analysis with Pandas

• The groupby Function
• Enhancing the groupby Function
• Challenge: Find the Weekly Sales Quantities
• The Pivot Table Function
• The Cut and Qcut Functions
• The "where" Function

 

9. Data Visualization with Pandas

• Histogram
• Line Plot
• Scatter Plot

 

10. Combining DataFrames with Pandas

• The Concat Function
• The Merge Function

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