🔥V1-Numpy- Create 1D & 2D Arrays | Python NumPy Tutorial –Beginners Guide with Examples
🔥 Learn Python NumPy from Scratch! Complete tutorial on creating 1D and 2D arrays with 100+ methods. Perfect for school students and beginners!
📚 WHAT YOU WILL LEARN:
✅ Create 1D and 2D arrays | np.arange, np.zeros, np.ones
✅ Generate random numbers | np.random
✅ Create identity matrices | Diagonal elements
✅ Linear space and intervals | Evenly spaced numbers
✅ Practical examples with code
⏱️ VIDEO TIMESTAMPS:
📚 INTRODUCTION (00:00 - 00:57)
00:00 - 100+ NumPy Methods Overview
00:15 - Array Creation, Math, Statistics
00:32 - Sorting, Searching, Comparison
00:41 - Reshape, Transpose, Matrix Operations
00:57 - Let's Start!
🔢 LESSON 1: NP.ARANGE - Create Arrays with Range (01:00 - 03:13)
01:00 - Creating Arrays | import numpy as np
01:03 - What is np.arange? | Range function for arrays
01:18 - Code: np.arange(5, 20) | Creates [5,6,7...19]
01:37 - Example: np.arange(5, 10) | Output [5,6,7,8,9]
01:55 - Code: np.arange(15, 20) | Output [15,16,17,18,19]
02:09 - Large Range: np.arange(1, 100) | Creates 1 to 99
02:31 - Step Interval: np.arange(0, 13, 3) | Output [0,3,6,9,12]
02:49 - Even Numbers: np.arange(0, 13, 2) | Output [0,2,4,6,8,10,12]
02:57 - Multiplication Table: np.arange(5, 51, 5) | Output [5,10,15...50]
03:13 - Function: np.arange(start, stop, step)
🔵 LESSON 2: NP.ZEROS - Arrays with Zeros (03:15 - 04:22)
03:19 - Code: np.zeros(3) | Output [0, 0, 0]
03:28 - Understanding: 1 row, 3 columns, all zeros
03:32 - 2D Array: np.zeros((5,5)) | 5 rows x 5 columns
03:51 - Parentheses Important | Use ((rows, cols)) for 2D
03:58 - Counting Structure | 5 rows, each has 5 columns
04:12 - Example: np.zeros((5,15)) | 5 rows, 15 columns
04:20 - Example: np.zeros((5,2)) | 5 rows, 2 columns
🔴 LESSON 3: NP.ONES - Arrays with Ones (04:22 - 04:58)
04:25 - Code: np.ones(3) | Output [1, 1, 1]
04:30 - Same as zeros but uses 1 instead of 0
04:34 - Code: np.ones((3,3)) | 3x3 array of ones
04:40 - Code: np.ones((6,3)) | 6 rows, 3 columns
04:46 - Code: np.ones((6,6)) | 6 rows, 6 columns
04:52 - Code: np.ones((6,10)) | 6 rows, 10 columns
📏 LESSON 4: NP.LINSPACE - Create Intervals (05:02 - 06:12)
05:07 - What is linspace? | Evenly spaced numbers
05:12 - Code: np.linspace(0, 10, 3) | Output [0, 5, 10]
05:24 - Code: np.linspace(0, 100, 10) | 10 equal points
05:34 - Output: [0, 11.11, 22.22, 33.33...100]
05:49 - Code: np.linspace(0, 100, 5)
05:59 - Output: [0, 25, 50, 75, 100] | 5 equal intervals
06:09 - Use When: You need exact number of points
06:12 - Function: np.linspace(start, end, num_points)
🆔 LESSON 5: NP.IDENTITY - Identity Matrix (06:17 - 07:10)
06:32 - What is Identity Matrix? | Diagonal = 1, Rest = 0
06:34 - Code: np.identity(4) | 4x4 identity matrix
06:43 - Diagonal Elements | [0,0]=1, [1,1]=1, [2,2]=1, [3,3]=1
06:54 - Code: np.identity(10) | 10x10 identity matrix
07:02 - Pattern | Only diagonal positions have 1
07:06 - Function: np.identity(n) | Creates nxn matrix
🎲 LESSON 6: NP.RANDOM - Random Numbers (07:10 - 09:28)
07:13 - Code: np.random.rand(2) | 2 random numbers (0 to 1)
07:22 - Output | Two random decimal numbers
07:27 - Code: np.random.rand(5,5) | 5x5 random array
07:34 - Code: np.random.rand(3,4) | 3 rows, 4 columns random
07:43 - All Values Different | Every number is random
07:51 - np.random.randn() | Normal distribution (skip for now)
08:08 - NP.RANDOM.RANDINT | Random integers in range
08:12 - Difference | rand=any, randint=specific range
08:16 - Code: np.random.randint(1, 100) | Random 1-99
08:27 - Example Output | 55
08:34 - Code: np.random.randint(98, 100) | Random 98-99
08:48 - Code: np.random.randint(85, 100) | Random 85-99
09:02 - Multiple Numbers | np.random.randint(1, 100, 10)
09:10 - Output | 10 random integers between 1-99
09:14 - Code: np.random.randint(90, 100, 10)
09:21 - Important | Upper limit excluded (100 not included)
09:25 - Function: np.random.randint(low, high, count)
🔜 NEXT VIDEO (09:28 - 09:45)
09:30 - Coming Soon | Array attributes, methods, reshape
09:42 - Thank You!
📚 KEY COMMANDS:
✅ np.arange(start, stop, step) - Range array
✅ np.zeros(shape) - Zero array
✅ np.ones(shape) - Ones array
✅ np.linspace(start, end, points) - Intervals
✅ np.identity(n) - Identity matrix
✅ np.random.rand(rows, cols) - Random decimals
✅ np.random.randint(low, high, count) - Random integers
🎯 Perfect for: School Students | Python Beginners | Class 11-12 | NumPy Learners | Data Science
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