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Data Manipulation in Python: Master Python, Numpy & Pandas

£25.00 ex Vat

Teacher

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Timothy Williams

Category:

  • Coding & Programming
  • Employability
  • Personal Development
4.8( 5 REVIEWS )
28 STUDENTS
Data Manipulation in Python: Master Python, Numpy & Pandas

Unlock the potential of Python with our comprehensive course, Data Manipulation in Python: Master Python, Numpy & Pandas. Whether you’re looking to refresh your Python knowledge or dive deeper into essential Python libraries for data science, this course has you covered. Start with a quick Python refresher to solidify your foundation.

Discover the power of NumPy, mastering its fundamental properties for numerical operations and learning how it integrates with Python’s robust capabilities. Develop a keen understanding of mathematics for data science, crucial for effective data manipulation in Python.

Explore the core of Python’s data analysis prowess with Pandas. You will gain insights into working with DataFrames and Series, essential for managing and analysing data efficiently. Delve into data cleaning techniques to prepare your datasets for analysis, a critical step in any data science endeavour.

Visualise data in Python, utilising its versatile plotting libraries to represent data insights clearly. Engage with exploratory data analysis to uncover patterns and relationships within your data, a key aspect of the Python data science workflow.

Finally, harness the power of Python for time series analysis, exploring methods to handle and analyse temporal data effectively. Join us to master Python and elevate your data manipulation skills to new heights, all within a theoretical framework designed for thorough comprehension.

This course is an excellent choice for anyone looking to enhance their Python proficiency for data manipulation and analysis. Enrol now to make the most of Python in your data science journey.

Your Benefits by Learning with ‘Cambridge Open Academy’:

  • Accreditation: Showcase your ability with our accredited Data Manipulation in Python: Master Python, Numpy & Pandas to potential employers.
  • Free Certificate: Get a Free Digital Certificate upon successful completion of the Data Manipulation in Python: Master Python, Numpy & Pandas.
  • Flexibility: Learn virtually from anywhere, anytime at your own pace and convenience.
  • Advance Your Career: Upskill to impress your employers and land your dream job or long-awaited promotion.
  • Immediately Applicable Coursework: Keep up with the latest skill trend by putting your skillsets to work.
  • Affordability: Save big with our online Data Manipulation in Python: Master Python, Numpy & Pandas as it not only suits your professional needs but also fits within your budget.
  • Tutor Support: Get tutor support on weekdays, 9-5 am, and our dedicated 24/7 customer support.
  • Lifetime Access: Achieve lifetime access to the top-notch expertly crafted course materials.

Our Specialised Delivery Method:

  • Interactive Learning Materials: The course modules were created using an EdTech industry-recognised tool to keep you engaged at all times. With this tool, you get interactive, engaging and top-notch course content. In our courses, you can take advantage of features like—
    • Drop Down Menu
    • Drag and Drop
    • Flash Card
    • Label Graphic
    • Timeline View
  • Responsiveness: In light of contemporary mobile and point-of-need learning trends, our courses are designed to be intrinsically dynamic and provide you the ultimate eLearning solution. These courses will adapt to any gadget without any extra software.
  • Learner-Friendly Navigation: Our courses are also quite simple to navigate for any learner. These courses are designed with simplicity and a modern flow that appeals to a wide range of learning audiences, regardless of their technical background and gadgets.
  • Elegant Outline: Our courses are visually appealing, where you can —
    • Track your progress on the left-side navigation toolbar.
    • Engage in drag-and-drop sorting activities and use the multiple response question to test your understanding of course topics.

With your newly acquired skills from this course can help you

  • Increase Your Hireability.
  • Make Yourself a Valuable Asset
  • Get Your Long-awaited Promotion.
  • Boost Your Pay-scale
  • Better Your Productivity

Certification:

Once you have successfully completed the Data Manipulation in Python: Master Python, Numpy & Pandas course, you will receive a PDF certificate completely free of cost as a proof of your accomplishment. The hardcopy certificate is also available for the cost of £9.99. UK students are required to pay a £10 as a delivery fee, while international students have to pay £19.99 for the shipment of a hardcopy certificate to their designated address.

Who is this course for?

This Data Manipulation in Python: Master Python, Numpy & Pandas course is developed for people who wish to excel in their professional and personal life. Learn from industry leaders and interact with a global network of experts by enrolling in this Data Manipulation in Python: Master Python, Numpy & Pandas course.

Requirements

Enrolling in our Data Manipulation in Python: Master Python, Numpy & Pandas course does not require any prior knowledge or experience. All that is required is an internet-connected gadget and a passion to learn.

Career Path

Participants in the Data Manipulation in Python: Master Python, Numpy & Pandas course are revolutionizing the professional landscape, propelling their careers forward, and enhancing their livelihoods across the globe. This sought-after course is empowering learners to forge new employment opportunities, advance within their respective industries, and experience substantial personal growth.

Python Quick Refresher (Optional)
Welcome to the course! 00:01:00
Introduction to Python 00:01:00
Course Materials 00:00:00
Setting up Python 00:02:00
What is Jupyter? 00:01:00
Anaconda Installation: Windows, Mac & Ubuntu 00:04:00
How to implement Python in Jupyter? 00:01:00
Managing Directories in Jupyter Notebook 00:03:00
Input/Output 00:02:00
Working with different datatypes 00:01:00
Variables 00:02:00
Arithmetic Operators 00:02:00
Comparison Operators 00:01:00
Logical Operators 00:03:00
Conditional statements 00:02:00
Loops 00:04:00
Sequences: Lists 00:03:00
Sequences: Dictionaries 00:03:00
Sequences: Tuples 00:01:00
Functions: Built-in Functions 00:01:00
Functions: User-defined Functions 00:04:00
Essential Python Libraries for Data Science
Installing Libraries 00:01:00
Importing Libraries 00:02:00
Pandas Library for Data Science 00:01:00
NumPy Library for Data Science 00:01:00
Pandas vs NumPy 00:01:00
Matplotlib Library for Data Science 00:01:00
Seaborn Library for Data Science 00:01:00
Fundamental NumPy Properties
Introduction to NumPy arrays 00:01:00
Creating NumPy arrays 00:06:00
Indexing NumPy arrays 00:06:00
Array shape 00:01:00
Iterating Over NumPy Arrays 00:05:00
Mathematics for Data Science
Basic NumPy arrays: zeros() 00:02:00
Basic NumPy arrays: ones() 00:01:00
Basic NumPy arrays: full() 00:01:00
Adding a scalar 00:02:00
Subtracting a scalar 00:01:00
Multiplying by a scalar 00:01:00
Dividing by a scalar 00:01:00
Raise to a power 00:01:00
Transpose 00:01:00
Element wise addition 00:02:00
Element wise subtraction 00:01:00
Element wise multiplication 00:01:00
Element wise division 00:01:00
Matrix multiplication 00:02:00
Statistics 00:03:00
Python Pandas DataFrames & Series
What is a Python Pandas DataFrame? 00:01:00
What is a Python Pandas Series? 00:01:00
DataFrame vs Series 00:01:00
Creating a DataFrame using lists 00:03:00
Creating a DataFrame using a dictionary 00:01:00
Loading CSV data into python 00:02:00
Changing the Index Column 00:01:00
Inplace 00:01:00
Examining the DataFrame: Head & Tail 00:01:00
Statistical summary of the DataFrame 00:01:00
Slicing rows using bracket operators 00:01:00
Indexing columns using bracket operators 00:01:00
Boolean list 00:01:00
Filtering Rows 00:01:00
Filtering rows using & and | operators 00:02:00
Filtering data using loc() 00:04:00
Filtering data using iloc() 00:02:00
Adding and deleting rows and columns 00:03:00
Sorting Values 00:02:00
Exporting and saving pandas DataFrames 00:02:00
Concatenating DataFrames 00:01:00
groupby() 00:03:00
Data Cleaning
Introduction to Data Cleaning 00:01:00
Quality of Data 00:01:00
Examples of Anomalies 00:01:00
Median-based Anomaly Detection 00:03:00
Mean-based anomaly detection 00:03:00
Z-score-based Anomaly Detection 00:03:00
Interquartile Range for Anomaly Detection 00:05:00
Dealing with missing values 00:06:00
Regular Expressions 00:07:00
Feature Scaling 00:03:00
Data Visualization using Python
Introduction 00:01:00
Setting Up Matplotlib 00:01:00
Plotting Line Plots using Matplotlib 00:02:00
Title, Labels & Legend 00:07:00
Plotting Histograms 00:01:00
Plotting Bar Charts 00:02:00
Plotting Pie Charts 00:03:00
Plotting Scatter Plots 00:06:00
Plotting Log Plots 00:01:00
Plotting Polar Plots 00:02:00
Handling Dates 00:01:00
Creating multiple subplots in one figure 00:03:00
Exploratory Data Analysis
Introduction 00:01:00
What is Exploratory Data Analysis? 00:01:00
Univariate Analysis 00:02:00
Univariate Analysis: Continuous Data 00:06:00
Univariate Analysis: Categorical Data 00:02:00
Bivariate analysis: Continuous & Continuous 00:05:00
Bivariate analysis: Categorical & Categorical 00:03:00
Bivariate analysis: Continuous & Categorical 00:02:00
Detecting Outliers 00:06:00
Categorical Variable Transformation 00:04:00
Time Series in Python
Introduction to Time Series 00:02:00
Getting Stock Data using Yfinance 00:03:00
Converting a Dataset into Time Series 00:04:00
Working with Time Series 00:04:00
Time Series Data Visualization with Python 00:03:00

Certification:​

Once you have successfully completed this course, you will receive a PDF certificate completely free of cost as a proof of your accomplishment. The hardcopy certificate is also available for the cost of £9.99.
Note: Delivery of hardcopy certificate is free within the United Kingdom. However, to obtain a hardcopy certificate, International students will have to pay additional fees based on their location.

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