Mastering Python, Pandas, Numpy for Absolute Beginners
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Are you ready to take your data analysis and manipulation skills to the next level? Welcome to “Mastering Data Manipulation with Python: A Comprehensive Guide to NumPy and Pandas.” In this hands-on course, you’ll embark on a journey to become a proficient data wrangler and analyst using the powerful tools at your disposal.
NumPy is a basic level external library in Python used for complex mathematical operations. NumPy overcomes slower executions with the use of multi-dimensional array objects. It has built-in functions for manipulating arrays. We can convert different algorithms to can into functions for applying on arrays. NumPy has applications that are not only limited to itself. It is a very diverse library and has a wide range of applications in other sectors. Numpy can be put to use along with Data Science, Data Analysis and Machine Learning. It is also a base for other python libraries. These libraries use the functionalities in NumPy to increase their capabilities.
This course introduce with all majority of concept of NumPy – numerical python library.
You will learn following topics :
1) Creating Arrays using Numpy in Python
2) Accessing Arrays using Numpy in Python
3) Finding Dimension of the Array using Numpy in Python
4) Negative Indexing on Arrays using Numpy in Python
5) Slicing an Array using Numpy in Python
6) Checking Datatype of an Array using Numpy in Python
7) Copying an Array using Numpy in Python
8) Iterating through arrays using Numpy in Python
9) Shape of Arrays using Numpy in Python
10) Reshaping Arrays using Numpy in Python
11) Joining Arrays using Numpy in Python
12) Splitting Array using Numpy in Python
13) Sorting an Array using Numpy in Python
14) Searching in Array using Numpy in Python
15) Filtering an Array using Numpy in Python
16) Generating a Random Array using Numpy in Python
The Numpy arrays are homogenous sets of elements. The most important feature of NumPy arrays is they are homogenous in nature. This differentiates them from python arrays. It maintains uniformity for mathematical operations that would not be possible with heterogeneous elements. Another benefit of using NumPy arrays is there are a large number of functions that are applicable to these arrays. These functions could not be performed when applied to python arrays due to their heterogeneous nature.
Course Highlights:
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Build a Strong Foundation: Whether you’re a beginner or looking to solidify your understanding, this course is designed to guide you from the basics to advanced data manipulation techniques.
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Master NumPy: Learn how to efficiently work with arrays, matrices, and perform mathematical operations using the NumPy library. Discover how to handle data of various dimensions effortlessly.
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Harness the Power of Pandas: Dive deep into Pandas, the go-to library for data manipulation in Python. Explore data structures like Series and DataFrames, and learn how to filter, reshape, and aggregate data effectively.
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Real-world Projects: Apply your newfound skills to real-world scenarios. Analyze and manipulate datasets, clean messy data, and extract valuable insights that drive informed decision-making.
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Optimize Your Workflow: Streamline your data analysis process by mastering techniques for data cleaning, transformation, and visualization, all while writing efficient and readable code.
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Unlock Data Insights: Learn how to manipulate, transform, and visualize data to uncover patterns and trends that tell a compelling data-driven story.
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Comprehensive Guidance: Benefit from step-by-step explanations, practical examples, and quizzes that reinforce your learning and ensure you grasp each concept.
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Lifetime Access: Gain unlimited access to course materials, allowing you to revisit and reinforce your skills whenever you need to.
Whether you’re a business analyst, data scientist, student, or anyone intrigued by the power of data, this course equips you with the tools to tackle data challenges with confidence. Join us now and unlock the potential of Python, NumPy, and Pandas to master the art of data manipulation.
Enroll today and take your data analysis skills to new heights!
Remember to personalize the course description based on the specific content, benefits, and approach of your course. Highlighting the practical skills learners will gain and the real-world applications of Python, NumPy, and Pandas will attract potential students.
Happy learning
Surendra Varma Pericherla
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1VariablesVideo lesson
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2Arithmetic Operators in PythonVideo lesson
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3Relational Operators in PythonVideo lesson
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4Logical Operators in PythonVideo lesson
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5Shortcut OperatorsVideo lesson
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6Bit-wise Operators in PythonVideo lesson
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7Type Conversion in PythonVideo lesson
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8Computing average of two given numbers in PythonVideo lesson
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9Computing area and circumference of circle in PythonVideo lesson
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10If StatementVideo lesson
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11Example program on if statementVideo lesson
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12If Else StatementVideo lesson
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13Example program on if else statementVideo lesson
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14Nested if StatementVideo lesson
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15Example program on Nested if StatementVideo lesson
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16Elif StatementVideo lesson
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17Example on Elif StatementVideo lesson
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18While Loop in PythonVideo lesson
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19For Loop in PythonVideo lesson
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20Program to compute sum of first 10 numbersVideo lesson
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21Program to compute Sum of digits in a given numberVideo lesson
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22Program to display numbers using for loopVideo lesson
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23Finding Factorial of a given numberVideo lesson
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24Using break and continue statementsVideo lesson
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31Basics of Strings in PythonVideo lesson
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32Concatenation of string and a numberVideo lesson
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33How to access a string in python using While LoopVideo lesson
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34Using For loop to work with StringsVideo lesson
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35Understanding String SlicingVideo lesson
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36Slicing String by leaving start/end positionVideo lesson
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37Program to Count all Letters, Digits & Special symbolsVideo lesson
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38Program to Count occurrences of character in StringVideo lesson
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39Program to Reverse a given StringVideo lesson
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40Program to remove Empty strings from given list of stringsVideo lesson
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41Functions in PythonVideo lesson
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42Example Program on FunctionsVideo lesson
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43Example Program on Functions in PythonVideo lesson
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44Example Program on FunctionsVideo lesson
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45Function to compute Cumulative Product of numbers in a ListVideo lesson
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46Function to Compute Duplicates in a ListVideo lesson
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47Modules in PythonVideo lesson
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48Computing GCD of two given numbers in PythonVideo lesson
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49Finding mean, median and mode on list of numbers in PythonVideo lesson
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50Online IDE for running Python Numpy programsVideo lesson
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51Creating & Accessing elements in 1D ArrayVideo lesson
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52Creating & Accessing elements in 2D ArrayVideo lesson
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53Finding Dimension of the ArrayVideo lesson
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54Using Negative Indexing to access elements in 1D arrayVideo lesson
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55Using Negative Indexing to access elements in 2D arrayVideo lesson
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56Slicing an ArrayVideo lesson
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57Checking Datatype of an ArrayVideo lesson
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58Copy Operation on an arrayVideo lesson
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59Iterating 1D arrayVideo lesson
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60Iterating 2D arrayVideo lesson
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61Finding Shape of the ArrayVideo lesson
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62Reshaping 1D Array to 2D ArrayVideo lesson
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63Joining Two ArraysVideo lesson
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64Splitting an ArrayVideo lesson
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65Sorting an ArrayVideo lesson
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66Searching for an Element in ArrayVideo lesson
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67Filtering an ArrayVideo lesson
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68Generate a Random IntegerVideo lesson
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69Generating a Random ArrayVideo lesson
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70Question #1Video lesson
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71Solution to Question #1Video lesson
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72Question #2Video lesson
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73Solution to Question #2Video lesson
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74Question #3Video lesson
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75Solution to Question #3Video lesson
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76Question #4Video lesson
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77Solution to Question #4Video lesson
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78Question #5Video lesson
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79Solution to Question #5Video lesson
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80Question #6Video lesson
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81Solution to Question #6Video lesson
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