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Advanced pandas—Going Beyond the Basics
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1.
Before We Begin
Course Introduction
2.
Reading Data into pandas
Importance of Data Ingestion
Read Data from the Web
Read Data from HTML Files
Read Data from XML Files
Read Data from Statistical Software Files
Read Data from SQL Databases
Read Data from Binary Files (Feather, HDF5, ORC, Parquet)
Quiz
3.
Combining Data
Importance of Combining Data
Concatenate
Merging—Types of Joins
Merge 2—Implementation
Merging—Scenarios
Combine and Update
Quiz
4.
Reshaping and Manipulating Data
Importance of Reshaping and Manipulating Data
GroupBy—The groupby() method
GroupBy—Aggregate
GroupBy—Transform and Filter
GroupBy—Further Useful Features
Pivot—Long and Wide Formats
Pivot—The pivot() method
Unpivot
Stack and Unstack
Further Reshaping Capabilities
Advanced Indexing 1
Advanced Indexing 2
Quiz
5.
Encoding Data Types
Inspect Data Types
Convert and Encode Data Types
6.
Handling Numerical Data
Arithmetic Operations 1
Arithmetic Operations 2
Comparison Operations
Filtering
Ordered Numerical Data
Discretize and Clip Data
Statistical Methods
Cumulative Operations
Apply Custom Functions
Quiz
7.
Handling Categorical Data
Encode Categorical Data
Modify Categorical Data
Comparison and Other Common Operations
Factorize and Cross-Tabulate
Other Features and Properties
Quiz
8.
Handling Text Data
Text Data Types
String Methods—Basic Transformations and Checks
String Methods—Slice, Split, and Partition
String Methods—Concatenate and Match
String Methods—Find, Extract, and Replace
String Methods—Leading and Trailing Characters
Quiz
9.
Handling Time Series Data
Time Series Data Types
Time Series Indexes—Creating Indexes
Time Series Indexes—Slice and Index
Time Series Indexes—Attributes
Time Series Indexes—Methods
Arithmetic Operations with Timedelta and DateOffset
Closer Look at Time Deltas
Business Dates and Holidays
Business Hours
Time Zones
Timeseries Merging
Resampling—Upsample and Downsample
Resampling—Aggregation and Other Parameters
Shifting and Frequency Conversion
Window Operations—Rolling
Window Operations—Weighted, Expanding, and Exponential Moving
Quiz
10.
Handling Sparse Data Structures
Sparse Arrays
Accessors and Operations
11.
Handling Missing Data
Missing Data Representation
Missing Data Detection and Calculations
Managing Missing Data
Quiz
Project
Premium
Data Analysis and Visualization with sidetable and Bokeh
12.
Leveraging Further Features of pandas
Function Chaining with pipe()
Assertion Functions
DataFrame Table Styles
Option Settings
Efficiency Boosts
Quiz
13.
Utilizing Extended Libraries
ydata-profiling
pandarallel
polars
pandasAI
Quiz
14.
Wrap Up
Conclusion
15.
Appendix
What's New in pandas 2.0
Setup Requirements
Overview of Statistical Software and Binary File Formats
Prerequisite Setup for Reading Data into pandas
Prerequisite Setup for Utilizing Extended Libraries
Project
Premium
Time Series Analysis and Visualization Using Python and Plotly
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Advanced pandas—Going Beyond the Basics
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Check your understanding of different data types that can be imported into pandas.
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