Mô tả

The course covers three key areas in Numpy:

  1. Numpy Arrays as Data Structures - Developing an in-depth understanding along the lines of:

    1. Intuition of Arrays as Data Containers

    2. Visualizing 2D/3D and higher dimensional Arrays

    3. Array Indexing and Slicing - 2D/3D Arrays

    4. Performing basic/advanced operations using Numpy Arrays


  2. Useful Numpy Functions - Basic to Advanced usage of the below Numpy functions and how they perform compared to their counterpart methods

    1. numpy where() function

      1. Comparison with Apply + Lambda

      2. Performance on Large DataFrames

      3. Varied uses in new variable creation

    2. numpy select() function

      1. Apply conditions on single and multiple numeric variables

      2. Apply conditions on categorical variable


  3. Array Broadcasting - Developing an intuition of "How Arrays with dissimilar shapes interact" and how to put it to use

    1. Intuition of Broadcasting concept on 2D/3D Arrays

    2. Under what scenarios can we use Broadcasting to replace some of the computationally expensive methods like For loops and Cross-join Operations, etc. especially when working on a large Datasets

The course also covers the topic - "How to time your codes/processes", which will equip you to:

  • Track time taken by any code block (using Two different methods) and also apply to your own processes/codes

  • Prepare for the upcoming Chapter "Useful Numpy Functions", where we not only compare performance of Numpy functions with other conventionally used methods but also monitor how they perform on large Datasets

Bạn sẽ học được gì

Develop understanding of how Arrays work and what advantages they offer over other Data Structures

Use Arrays as Data containers for common data operations

Compare time performance of your process codes versus a suitable Numpy function

In-depth understanding to use numpy's where() and select() functions to replace conventionally used methods

Apply Array Broadcasting in your line of work to replace Nested For loops and Cross-join operations

Yêu cầu

  • Basic knowledge of Python (including Data Types and Structures, Control Flow, Functions, etc.)
  • Basic knowledge of Pandas

Nội dung khoá học

5 sections

Introduction to Numpy Library and Arrays

3 lectures
Overview of Numpy Library
03:13
Overview of Numpy Arrays (sample)
03:55
Overview of Numpy Arrays
12:17

Numpy Arrays

14 lectures
Array Basics Part 1 of 2
12:10
Quiz 2.1
3 questions
Array Basics Part 2 of 2
10:39
Quiz 2.2
5 questions
Arrays as Data Containers (sample)
02:05
Arrays as Data Containers
07:40
Visualizing Arrays
04:18
Array Indexing and Slicing Part 1 of 2
04:30
Array Indexing and Slicing Part 2 of 2
11:13
Quiz 2.3
6 questions
3D Array Indexing and Slicing
13:14
Quiz 2.4
3 questions
Basic Array Operations
11:08
Chapter 02 Assignment
5 questions

Timing the code

7 lectures
Chapter Introduction : Timing the Code
01:07
Timing Codes : Popular Methods
02:39
Quiz 3.1
3 questions
Comparing how Arrays perform versus a List (for the same operation)
10:17
Quiz 3.2
2 questions
Comparing Binning methods performance : Numpy digitige() Function versus Others
13:36
Quiz 3.3
3 questions

Numpy Functions

9 lectures
Chapter Introduction : Numpy Functions
01:24
np.where() function overview
01:37
np.where() function performance versus Apply + Lambda
13:10
np.where() performance with increasing DataFrame size
09:53
Various uses of np.where() Function
13:03
np.select() function overview
02:36
np.select() function : Application in Flooring/Capping (Basic)
05:38
np.select() function : Application in Flooring/Capping (Advanced)
10:42
np.select() function : Application on a categorical variable
06:55

Array Broadcasting

8 lectures
Chapter Introduction : Array Broadcasting
01:36
Broadcasting Intuition : 2D Arrays Example
03:08
Laying down Broadcasting rules for a 2D Array
08:14
Practical Application 01 : Simple operations on Multiple Variables
13:54
Practical Application 02 : Flooring/Capping with different threshold values
08:37
Practical Application 03 : Broadcasting as an Alternate to Cross-join
15:55
Broadcasting Intuition : 3D Array Example
08:20
Practical Application 04 : Finding closest centroid
09:01

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