Complete Python Masterclass for Data Visualisation
5 Students
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1 Year
Access -
Intermediate
Skill Level -
Course Certificate
Certificate -
50
Units -
0
Quizzes -
3 hours, 45 minutes
Duration
Overview
Data visualisation is an integral part of Data Science. Programming Language Python is used to visualise any given data. Unlock your proficiency in the realm of data with our Complete Python Masterclass for Data Visualisation.
This masterclass course will significantly focus on Matplotlib – a comprehensive library for creating static, animated, and interactive visualizations in Python. Firstly, you will taught about the setup and installation of Anaconda Navigator and Matplotlib. Secondly, you will learn to utilise Matplotlib to plot Line Plots, Histograms etc, followed by Time Series Data Visualisation. Finally, the course will end with the installation and setup of Plotly and Cufflinks, preceded by two other modules.
At the end of the course, you will receive a certificate of achievement. This certificate will enhance your employability in the IT industry. Join now!
Course Preview
Learning Outcomes
- Learn to install and set up Anaconda Navigator and Matplotlib
- Master the plotting of line plots, histograms, and scatter plots
- Gain proficiency in Bar chart visualisation
- Develop the ability to handle and visualize time series data
- Understand the use of Seaborn for creating eye-pleasing plots
- Explore the capabilities of Plotly and Cufflinks for interactive visualizations
Why Take This Course From John Academy?
- Affordable, well-structured and high-quality e-learning study materials
- Meticulously crafted, engaging and informative tutorial videos and materials
- Efficient exam systems for the assessment and instant result
- Earn UK & internationally recognised accredited qualification
- Easily access the course content on mobile, tablet, or desktop from anywhere, anytime
- Excellent career advancement opportunities
- Get 24/7 student support via email
What Skills Will You Learn from This Course?
- Python Environment Setup for Data Visualisation
- Basic to Advanced Plotting with Matplotlib
- Time Series Data Visualization
- Creating Visualisations with Seaborn
- Interactive Plots with Plotly and Cufflinks
Who Should Take This Complete Python Masterclass for Data Visualisation?
Whether you’re an existing practitioner or an aspiring professional, this course is an ideal training opportunity. It will elevate your expertise and boost your CV with key skills and a recognised qualification attesting to your knowledge.
Are There Any Entry Requirements?
This Complete Python Masterclass for Data Visualisation is available to all learners of all academic backgrounds. But learners should be aged 16 or over to undertake the qualification. And a good understanding of the English language, numeracy, and ICT will be helpful.
Complete Python Masterclass for Data Visualisation Certification
After completing and passing the Complete Python Masterclass for Data Visualisation course successfully, you will be able to obtain a Recognised Certificate of Achievement. Learners can obtain the certificate in hard copy at £14.99 or PDF format at £11.99.
Career Path
This exclusive Complete Python Masterclass for Data Visualisation will equip you with effective skills and abilities and help you explore career paths such as
- Data Analyst
- Business Intelligence Analyst
- Reseach Analyst
- Data Scientist
- Data Visualisation Specialist
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Introduction to seaborn 00:02:00
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Installation and Setup 00:02:00
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3D plots, spread plot and hist plot, bubble plot, and heatmap 00:07:00
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Adding a grid to the chart 00:04:00
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Adding a legend 00:04:00
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Adding edges to dots 00:04:00
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Adding legends, titles, location and rotating pie chart 00:06:00
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Adding median to histogram 00:04:00
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Advanced Histograms and Patches (Part 1) 00:04:00
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Advanced Histograms and Patches (Part 2) 00:05:00
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Cat plots 00:03:00
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Changing colors of markers 00:06:00
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Changing colors, linestyles, linewidth and markers 00:09:00
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Changing edge color and adding shadow on the edge 00:04:00
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Changing edge colour of the histogram 00:03:00
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Changing fill color of different areas (negative vs positive for example) 00:03:00
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Changing the axis scale to log scale 00:07:00
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Changing the axis scales 00:06:00
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Changing the size of the dots 00:06:00
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Connecting data points by line 00:04:00
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Controlling Plotted Figure Aesthetics 00:03:00
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Converting string dates using the .to_datetime() pandas method 00:05:00
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Creating Box and Whisker Plots 00:11:00
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Explaining Matplotlib libraries apart 00:07:00
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Filling area on line plots and filling only specific area 00:04:00
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Filling only a specific area 00:07:00
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Getting separate figures 00:03:00
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Histograms vs Bar charts (Part 1) 00:03:00
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Histograms vs Bar charts (Part 2) 00:02:00
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Installing Matplotlib, seaborn & cufflinksv 00:03:00
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Installing the Anaconda Navigator 00:07:00
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Jointplot, pair plot and regression plot 00:02:00
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Label Styling 00:04:00
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Line plots 00:02:00
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Line, Scatter, Bar, box and area plot 00:07:00
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Overlaying bar plots on top of each other (Part 1) 00:04:00
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Overlaying bar plots on top of each other (Part 2) 00:01:00
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Plotting a basic scatter plot 00:06:00
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Plotting a basic stack plot 00:13:00
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Working on hue, style and size in seaborn 00:05:00
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Plotting a stack plot od data with constant total 00:04:00
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Plotting a stem plot 00:05:00
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Plotting live data using FuncAnimation in matplotlib 00:04:00
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Plotting multiple plots in one figure 00:02:00
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Reading data from a csv file with pandas 00:03:00
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Saving figures to your computer 00:03:00
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Setting up the number of rows and columns 00:04:00
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Subplots using seaborn 00:05:00
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Using the Python datetime module 00:03:00
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