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Data Manipulation: Python, Numpy and Pandas Overview

Ever feel overwhelmed by the sheer amount of data companies collect? What if you could transform this data into actionable insights that drive real results? This course empowers you to do just that!

We’ll guide you step-by-step through the essential tools and techniques of data science, all powered by the popular and beginner-friendly programming language, Python. Regardless of your current Python experience, this course bridges the gap. Whether you’re a complete novice or looking to refresh your skills, we’ll equip you to leverage the power of industry-standard libraries like NumPy and Pandas.

These libraries are your secret weapons for data manipulation. Imagine effortlessly organizing messy datasets, cleaning and filtering out inconsistencies, and preparing them for in-depth analysis. With newfound clarity, you’ll be able to create compelling charts and graphs, revealing hidden patterns and trends within the data.

Whether you’re a complete beginner or a seasoned professional looking to refine your data science skills, this course sets you on the path to success. It equips you with the foundational knowledge and practical skills to embark on a rewarding career in data science, a field with ever-growing demand and opportunities.

This course is your gateway to a world of possibilities. Enrol today and take the first step towards transforming data into a powerful tool for progress.

Learning Outcomes:

  • Master the fundamentals of data manipulation using Python libraries.
  • Gain expertise in wrangling and cleaning messy datasets.
  • Craft compelling data visualizations to communicate insights effectively.
  • Conduct exploratory data analysis to uncover hidden trends and patterns.
  • Work confidently with time series data for insightful forecasting.

Why You Should Choose Data Manipulation: Python, Numpy and Pandas

  • Lifetime access to the course
  • No hidden fees or exam charges
  • CPD Accredited certification on successful completion
  • Full Tutor support on weekdays (Monday – Friday)
  • Efficient exam system, assessment and instant results
  • Download Printable PDF certificate immediately after completion
  • Obtain the original print copy of your certificate, dispatch the next working day for as little as £9.
  • Improve your chance of gaining professional skills and better earning potential.

Who is this Course for?

Data Manipulation: Python, Numpy and Pandas is CPD certified and IAO accredited. This makes it perfect for anyone trying to learn potential professional skills.

As there is no experience and qualification required for this course, it is available for all students from any academic backgrounds.

Requirements

Our Data Manipulation: Python, Numpy and Pandas is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation.

Career Path

You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas’ are CPD and IAO accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume.

Course Curriculum

Data Manipulation: Python, Numpy and Pandas
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
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 00:05:00
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 00:03:00
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

FAQs

This course is for anyone who's interested in this topic and wants to learn more about it. This course will also help you gain potential professional skills.

No prior qualifications are needed to take this course.

You can study this course from wherever and whenever you want. You can study at your own pace and from any device. Just log in to your account from any device and start learning!

Yes, there is a test at the end of the course. Once you’ve completed all the modules of the course, you will have to give a multiple-choice test. The questions will be based on the topics of the modules you studied. And of course, you can take the test at any time, from any device and from anywhere you want.

Don’t worry if you fail the test, you can retake it as many times as you want.

You don’t have to wait a minute after your payment has been received, you can begin immediately. You will create your login details during the checkout process and we will also send you an email confirming your login details.

We make the payment process easy for you. You can either use your Visa, MasterCard, American Express, Solo cards or PayPal account to pay for the online course. We use the latest SSL encryption for all transactions, so your order is safe and secure.

After you complete the course, you’ll immediately receive a free printable PDF certificate. Hard Copy certificate is also available, and you can get one for just £9! You may have to wait for 3 to 9 days to get the hard copy certificate.

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