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Journey into Data Science with Python
Intro to Data Visualization with Titanic
Intro to Data Visualization with Titanic
An in-depth advanced course dedicated to mastering data visualization techniques using Python, Matplotlib, and Seaborn. You will get to work with a real-world Titanic dataset and explore critical aspects of data representation and interpretation.
Lessons and practices
Lesson 1: Deep Exploration of the Titanic Dataset: Features and Characteristics
Exploring the Titanic Dataset with Pandas Functions
Diving Deeper into Titanic Dataset Rows
Debugging Titanic Dataset Exploration
Exploring Unique Entries in Titanic Dataset
Exploring Unique Values of 'Embarked' in Titanic Data
Exploring Titanic Dataset: Add Missing Code Pieces
Exploring the Titanic Dataset from Scratch
Lesson 2: Diving into Descriptive Statistics of The Titanic Dataset
Exploring the Titanic Dataset with Descriptive Statistics
Applying Descriptive Statistics to Different Column
Debug the Descriptive Statistics Calculation
Calculating Median and Mode for 'Age' in the Titanic Dataset
Generating Descriptive Statistics for the Titanic Dataset
Adding Descriptive Statistics and Calculating the Interquartile Range for Age
Exploring Age Statistics in the Titanic Dataset
Lesson 3: Extending Data Visualization: Enhancing Plots and Analyzing with Matplotlib
Visualizing Gender Distribution in the Titanic Dataset Using Matplotlib
Exploring Passenger Class Distribution
Plotting a Course Correction: Fixing Bar Chart in Pandas
Discovering the Distribution of Titanic's Passenger Classes
Crafting the 'Sex Distribution' Bar Plot
Lesson 4: Unleashing Aesthetics in Visualization: An Introduction to Seaborn's Styling Capabilities
Visualizing the Data with Aesthetics and Styling through Seaborn
Changing the Variable for the Count Plot
Debugging Seaborn Countplot Generation
Craft Your First Seaborn Plot
Styling and Customizing a Seaborn Countplot from Scratch
Lesson 5: Visualizing Distributions with Histograms Using Seaborn
Visualizing Age Distribution with a Histogram in Seaborn
Refining Age Distribution with Granular Bin Widths
Fix the Histogram Plotting Code
Creating a Histogram with KDE for Age Distribution
Adding Titanic Passengers' Age Distribution to Seaborn Histograms
Creating a Histogram with KDE for Age Distribution in Titanic Dataset
Lesson 6: Visualizing Categorical Relations with Bar Plots
Visualizing Gender and Survival Rates with Bar Plots
Tweaking the Code: Visualizing Passenger Class and Survival Correlation
Correcting The Survival Rate Visualization
Adding and Displaying a Countplot in Seaborn
Mastering Bar Plots for Categorical Relations
Lesson 7: Exploring Multivariate Relationships: Scatter Plots and Correlations in Data Visualization
Visualizing with Scatter Plots: Age vs Fare in Titanic Dataset
Changing Marker Style in Scatter Plot
Fixing the Scatter Plot for Titanic Dataset
Adding Scatter Plot and Correlation Matrix Calculation
Implementing Scatter Plot and Correlation Functionality
Scatter Plot with Extra Dimensions and Correlation Calculation
Lesson 8: Analyzing Relationships between Passenger Class, Fare, and Survival with Box Plots
Exploring Ticket Fares and Passenger Classes Using Box Plots
Switching Orientation of Your Box Plot
Fixing Passenger Class Analysis with Box Plot
Constructing Seaborn Box Plots with Titanic Dataset Survival Analysis
Box Plot Creation and Customization
Unveil the Relationships: Constructing a Box Plot for the Titanic Dataset
Lesson 9: Unlocking Insights with Heatmaps: Correlation Analysis in Data Visualization
Discovering Correlations with a Heatmap
Creating a Heatmap with a Custom Color Map
Correcting the Heatmap Visualization
Adding Heatmap for Correlation Matrix
Visualizing Correlation Matrix using Seaborn Heatmap
Creating a Heatmap for the Titanic Dataset Correlation Matrix
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