on-demand course

Data Analysis with Pandas and Python

with Boris Paskhaver

February 2024

Beginner to intermediate

19h 26m

English

Packt Publishing

Closed Captioning available in English, Spanish

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Course outline

Introduction to the Course
11m 14s
macOS - Download and Install the Anaconda Distribution
4m 2s
Windows - Download and Install the Anaconda Distribution
4m 12s
Use Anaconda Navigator to Create a New Environment
10m 25s
Unpack Course Materials + The Startdown and Shutdown Process
11m 31s
Intro to the Jupyter Lab Interface
10m 24s
Code Cell Execution
14m 24s
Import Libraries into Jupyter Lab
8m 14s
Comments
8m 10s
Basic Data Types
15m 1s
Operators
20m 50s
Variables
12m 40s
Built-in Functions
8m 41s
Custom Functions
19m 58s
String Methods
25m 29s
Lists
15m 26s
Index Positions and Slicing
18m 19s
Dictionaries
17m 26s
Classes
10m 10s
Navigating Libraries using Jupyter Lab
12m 9s
Create a Series Object from a List
10m 15s
Create a Series Object from a Dictionary
4m 52s
Intro to Series Methods
4m 37s
Intro to Attributes
11m 8s
Parameters and Arguments
14m 33s
Import Series with the pd.read_csv Function
22m 42s
The head and tail Methods
3m 14s
Passing Series to Python Built-In Functions
6m 58s
Check for Inclusion with Python's in Keyword
6m 43s
The sort_values Method
6m 39s
The sort_index Method
4m 54s
Extract Series Values by Index Position
10m 39s
Extract Series Values by Index Label
6m 19s
The get Method
7m 24s
Overwrite a Series Value
6m 56s
The copy Method
10m 39s
Math Methods on Series Objects
6m 32s
Broadcasting
3m 57s
The value_counts Method
5m 14s
The apply Method
7m 45s
The map Method
9m 27s
Methods and Attributes between Series and DataFrames
18m 32s
Differences between Shared Methods
7m 36s
Select One Column from a DataFrame
10m 5s
Select Multiple Columns from a DataFrame
4m 41s
Add New Column to DataFrame
10m 49s
A Review of the value_counts Method
2m 58s
Drop DataFrame Rows with Missing Values
7m 52s
Fill in Missing Values with the fillna Method
7m 22s
The astype Method I
7m 29s
The astype Method II
7m 47s
Sort a DataFrame with the sort_values Method I
7m 50s
Sort a DataFrame with the sort_values Method II
12m 14s
Sort DataFrame with the sort_index Method
3m 28s
Rank Series Values with the rank Method
6m 31s
This Module's Dataset + Memory Optimization
19m 41s
Filter a DataFrame Based on a Condition
15m 1s
Filter with More than One Condition (AND - &)
8m 51s
Filter with More than One Condition (OR - |)
10m 28s
The isin Method
4m 39s
The isnull and notnull Methods
3m 55s
The between Method
6m 7s
The duplicated Method
9m 43s
The drop_duplicates Method
11m 7s
The unique and nunique Methods
4m 33s
This Module's Dataset
2m 20s
The set_index and reset_index Methods
10m 32s
Retrieve Rows by Index Position with iloc Accessor
5m 8s
Retrieve Rows by Index Label with loc Accessor
10m 3s
Second Arguments to loc and iloc Accessors
10m 16s
Overwrite Value in a DataFrame
8m 1s
Overwrite Multiple Values in a DataFrame
9m 59s
Rename Index Labels or Columns in a DataFrame
8m 52s
Delete Rows or Columns from a DataFrame
6m 57s
Create Random Sample with the sample Method
2m 47s
The nsmallest and nlargest Methods
7m 31s
Filtering with the where Method
4m 3s
The apply Method with DataFrames
13m 34s
This Module's Dataset
5m 30s
Common String Methods
8m 33s
Filtering with String Methods
6m 33s
String Methods on Index and Columns
4m 28s
The split Method
5m 6s
More Practice with Splits
7m 20s
The expand and n Parameters of the split Method
7m 55s
Intro to the MultiIndex Module
5m 26s
Create a MultiIndex
13m 58s
Extract Index Level Values
3m 58s
Rename Index Lebels
4m 43s
The sort_index Method on a MultiIndex DataFrame
6m 15s
Extract Rows from a MultiIndex DataFrame
19m 10s
The transpose Method
3m 11s
The stack Method
9m 2s
The unstack Method
11m 43s
The pivot Method
10m 50s
The melt Method
8m 13s
The pivot_table Method
13m 35s
Intro to the GroupBy Module
3m 17s
The groupby Method
8m 11s
Retrieve A Group with the get_group Method
2m 31s
Methods on the GroupBy Object
7m 4s
Grouping by Multiple Columns
4m 51s
The agg Method
3m 31s
Iterating through Groups
7m 26s
Intro to the Merging DataFrames Module
6m 19s
The pd.concat Function I
8m 34s
The pd.concat Function II
9m 21s
Left Joins
7m 45s
The left_on and right_on Parameters
6m 41s
Inner Joins I
10m 0s
Inner Joins II
8m 20s
Full-Outer Joins
9m 16s
Merging by Indexes with the left_index and right_index Parameters
7m 3s
The join Method
4m 2s

Content preview from Data Analysis with Pandas and Python

Intro to the Working with Dates and Times Module and Review of Python's datetime

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Publisher Resources

ISBN: 9781788622394Supplemental Content

Data Analysis with Pandas and Python

with Boris Paskhaver

Chapter 1 : Installation and Setup

Chapter 2 : Python Crash Course

Chapter 3 : Series

Chapter 4 : DataFrames I: Introduction

Chapter 5 : DataFrames II: Filtering Data

Chapter 6 : DataFrames III: Data Extraction

Chapter 7 : Working with Text Data

Chapter 8 : MultiIndex

Chapter 9 : GroupBy

Chapter 10 : Merging DataFrames

Chapter 11 : Working with Dates and Times

Chapter 12 : Input and Output

Chapter 13 : Visualization

Chapter 14 : Options and Settings

Chapter 15 : Conclusion

Content preview from Data Analysis with Pandas and Python

Intro to the Working with Dates and Times Module and Review of Python's datetime

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.