Curriculum
13 Sections
103 Lessons
15 Hours
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Section 1: Getting Started
7
1.1
Course Introduction
4 Minutes
1.2
How To Get Most Out Of This Course
2 Minutes
1.3
Better To Know These Things
3 Minutes
1.4
How to Install Python Ipython And Jupyter Notebook
9 Minutes
1.5
How To Install Anaconda For Macos And Linux Users
7 Minutes
1.6
How To Work With The Jupyter Notebook Part 1
16 Minutes
1.7
How To Work With The Jupyter Notebook Part 2
11 Minutes
Section 2: Pandas Building Blocks
2
2.1
How To Work With The Tabular Data
5 Minutes
2.2
How To Read The Documentation In Pandas
14 Minutes
Section 3: Pandas Data Structures
4
3.1
How To Construct The Pandas Series
12 Minutes
3.2
How To Construct The Dataframe Objects
13 Minutes
3.3
How To Construct The Pandas Index Objects
12 Minutes
3.4
Theory On Pandas Data Structures
6 Minutes
Section 4: Data Indexing And Selection
7
4.1
Data Selection In Series Part 1
6 Minutes
4.2
Indexers Loc And Iloc In Series
12 Minutes
4.3
Data Selection In Series Part 2
2 Minutes
4.4
Data Selection In Dataframe Part 2
4 Minutes
4.5
Theory On Data Indexing And Selection
6 Minutes
4.6
Accessing Values Using Loc Iloc And Ix In Dataframe Objects
9 Minutes
4.7
Data Selection In Dataframe Part 1
5 Minutes
Section 5: Essential Functionalities
11
5.1
How To Reindex Pandas Objects
12 Minutes
5.2
How To Drop Entries From An Axis
8 Minutes
5.3
Arithmetic And Data Alignment
7 Minutes
5.4
Arithmetic Methods With Fill Values
15 Minutes
5.5
Broadcasting In Pandas
7 Minutes
5.6
Apply And Applymap In Pandas
8 Minutes
5.7
How To Sort And Rank In Pandas
13 Minutes
5.8
How To Work With The Duplicated Indices
4 Minutes
5.9
Summarisig And Computing Descriptive Statistics
7 Minutes
5.10
Unique Values Value Counts And Membership
12 Minutes
5.11
Theory On Essential Functionalities
10 Minutes
Section 6: Data Handling
6
6.1
How To Read The Csv Files Part-1
19 Minutes
6.2
How To Read The Csv Files Part-2
15 Minutes
6.3
How To Read Text Files In Pieces
7 Minutes
6.4
How To Export Data In Text Format
10 Minutes
6.5
How To Use Python_s Csv Module
6.6
Theory On Data Handling
4 Minutes
Section 7: Data Cleaning And Preparation
15
7.1
How To Handle Missing Values
9 Minutes
7.2
How To Filter The Missing Values
9 Minutes
7.3
How To Filter The Missing Values Part 2
9 Minutes
7.4
How To Remove Duplicate Rows And Values
12 Minutes
7.5
How To Replace The Non Null Values
9 Minutes
7.6
How To Rename The Axis Labels
7 Minutes
7.7
How To Descretize And Bin The Data
22 Minutes
7.8
How To Filter And Detect The Outliers
4 Minutes
7.9
How To Reorder And Select Randomly
7 Minutes
7.10
Converting The Categorical Variables Into Dummy Variables
10 Minutes
7.11
How To Use _map_ Method
7 Minutes
7.12
How To Manipulate With Strings
13 Minutes
7.13
Using Regular Expressions
20 Minutes
7.14
Working With The Vectorized String Functions
9 Minutes
7.15
Theory On Data Preprocessing
11 Minutes
Section 8: Data Wrangling
10
8.1
Hierarchical Indexing-1
8 Minutes
8.2
Hierarchical Indexing Reordering And Sorting-2
7 Minutes
8.3
Summary Statistics By Level-3
3 Minutes
8.4
Hierarchical Indexing With Dataframe Columns-4
5 Minutes
8.5
How To Merge The Pandas Objects-1
20 Minutes
8.6
Merging On Row Index-2
13 Minutes
8.7
How To Concatenate Along An Axis-3
19 Minutes
8.8
How To Combine With Overlap-4
7 Minutes
8.9
How To Reshape And Pivot Data In Pandas-5
9 Minutes
8.10
Theory On Data Wrangling
8 Minutes
Section 9: Data Grouping And Aggregation
7
9.1
Groupby Operation
16 Minutes
9.2
How To Iterate Over Groupby Object
6 Minutes
9.3
How To Select Columns In Groupby Method
3 Minutes
9.4
Grouping Using Dictionaries And Series
3 Minutes
9.5
Grouping Using Functions And Index Level
5 Minutes
9.6
Data Aggregation
10 Minutes
9.7
Thoery On Data Group by And Aggregation
4 Minutes
Section 10: Time Series Analysis
8
10.1
Introduction To Time Series Data Types
10 Minutes
10.2
How To Convert Between String And Datetime
15 Minutes
10.3
Time Series Basics With Pandas Objects
13 Minutes
10.4
Date Ranges Frequencies And Shifting Part 1
11 Minutes
10.5
Date Ranges Frequencies And Shifting Part 2
11 Minutes
10.6
Time Zone Handling
9 Minutes
10.7
Periods And Period Arithmetics
11 Minutes
10.8
Thoery On Time Series Analysis
6 Minutes
EXERCISE VIDEOS
Here you will get practical knowledge with respect to all the lessons you have learnt so far.
16
11.1
Practice Part 1
4 Minutes
11.2
Practice Part 1 Solution
22 Minutes
11.3
Practice Part 2
3 Minutes
11.4
Practice Part 2 Solution
13 Minutes
11.5
Practice Part 3
3 Minutes
11.6
Practice Part 3 Solution
17 Minutes
11.7
Practice Part 4
3 Minutes
11.8
Practice Part 4 Solution
15 Minutes
11.9
Practice Part 5
2 Minutes
11.10
Practice Part 5 Solution
15 Minutes
11.11
Practice Part 6
1 Minute
11.12
Practice Part 6 Solution
6 Minutes
11.13
Practice Part 7
3 Minutes
11.14
Practice Part 7 Solution
13 Minutes
11.15
Practice Part 8
3 Minutes
11.16
Practice Part 8 Solution
12 Minutes
PROJECT VIDEOS
This section is related to projects on Padas and you will be able to work with the Industry oriented standard projects to analyse the data. Once you finish this section you'll be able to handle the projects on your own.
9
12.1
A Brief Introduction To The Pandas Projects
11 Minutes
12.2
Project 1 Description
5 Minutes
12.3
Project 1 Solution Part 1
17 Minutes
12.4
Project 1 Solution Part 2
14 Minutes
12.5
Project 2 Description
2 Minutes
12.6
Project 2 Solution Part 1
19 Minutes
12.7
Project 3 Description
3 Minutes
12.8
Project 3 Solution Part 1
12 Minutes
12.9
Project 3 Solution Part 2
12 Minutes
RESOURCE FILES
1
13.1
Links to view resource files
15 Minutes
Python For Data Analysis and Data Science Zero To Mastery With Pandas
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How To Read The Documentation In Pandas
https://dwnk32xmy75f1.cloudfront.net/wp-content/uploads/20210502143923/9_How-To-Read-The-Documentation-In-Pandas.mp4
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