Python provides a myriad of data visualization libraries that give you the flexibility to define every aspect of your visualization. It provides you the option of choosing between static images, which can be helpful for academic papers, and interactive visualizations that can help you delve deeper into your data.

## Data Visualization with Python using Seaborn

- Creating Pair Plots in Seaborn with sns pairplotIn this tutorial, you’ll learn how to create pair plots in Seaborn, using the sns.pairplot() function. These visualizations plot pairwise relationships in a dataset so that each variable in a dataset will be plotted against each other variable in the dataset. This allows you to easily visualize the relationships between pairs of variables. Seaborn is… Read More »Creating Pair Plots in Seaborn with sns pairplot
- Numpy Normal (Gaussian) Distribution (Numpy Random Normal)In this tutorial, you’ll learn how to use the Numpy random.normal function to create normal (or Gaussian) distributions. The functions provides you with tools that allow you create distributions with specific means and standard distributions. Additionally, you can create distributions of different sizes. By the end of this tutorial, you’ll have learned: What the normal… Read More »Numpy Normal (Gaussian) Distribution (Numpy Random Normal)
- How to Calculate Mean Squared Error in PythonThe mean squared error is a common way to measure the prediction accuracy of a model. In this tutorial, you’ll learn how to calculate the mean squared error in Python. You’ll start off by learning what the mean squared error represents. Then you’ll learn how to do this using Scikit-Learn (sklean), Numpy, as well as… Read More »How to Calculate Mean Squared Error in Python
- Seaborn Boxplot – How to Create Box and Whisker PlotsLearn how to create a Seaborn boxplot, including how to add styles, titles, axis labels and add grouped boxplots.
- Seaborn Line Plot – Create Lineplots with Seaborn relplotLearn how to use the Seaborn line plot andrelplot functions to create beautiful line charts, add titles, customize styles, multiple line charts.
- Seaborn Barplot – Make Bar Charts with sns.barplotLearn how to use the Seaborn barplot and countplot functions to create beautiful bar charts, add titles, customize styles, group bar charts.
- Seaborn in Python for Data VisualizationIn this tutorial, you’ll learn how to create a wide variety of different plots using Seaborn, as well as how to apply different styling options to these plots.
- Plotting a Histogram in Python with Matplotlib and PandasLearn what histograms are and how to create them in Python with Matplotlib and Pandas.

## Data Visualization with Python using Matplotlib

- How to Create 3D Scatterplots in MatplotlibIn this tutorial, you’ll learn how to make 3D scatterplots using Matplotlib. Being able to visualize data in three dimensions can be an important step in clearly articulating data, especially in science and machine learning. By the end of this tutorial, you’ll have learned: How to plots 3D scatterplots using Matplotlib How to change size, opacity, and color of data points in three dimensions How to add titles and axis labels to your 3D scatterplot in Matplotlib Creating a 3D Scatterplot in Matplotlib In order to create 3D scatterplots in Matplotlib we can import some additional helper modules from Matplotlib.… Read More »How to Create 3D Scatterplots in Matplotlib
- How to Change Font Size in Matplotlib PlotIn this tutorial, you’ll learn how to change font sizes on a Matplotlib plot. You’ll learn everything you need to know to customize your Matplotlib plot to have exactly the font sizes you want. Data visualization is an incredible tool to better communicate your data. Being able to style your plot in the way you want is an important part of that. By the end of this tutorial, you’ll have learned: How to change font sizes globally in Matplotlib How to change font sizes of titles, axis labels, and tick labels Change font sizes using rc parameters Resetting font sizes… Read More »How to Change Font Size in Matplotlib Plot
- Set Marker Size in Matplotlib ScatterplotsIn this tutorial, you’ll learn how to define and set the marker size in Matplotlib scatterplots. Being able to control the size of your Matplotlib scatterplots allows you to add extra information to your scatterplots. This allows you to communicate more details about your data and make it clearer to your visualization’s readers. Matplotlib allows you to customize the size for all plots as well as for individual plots, based on other data criteria. By the end of this tutorial, you’ll have learned: How to set the marker size for all points in a Matplotlib scatterplot How to set the… Read More »Set Marker Size in Matplotlib Scatterplots
- How to Change Plot and Figure Size in MatplotlibIn this tutorial, you’ll learn how to change the plot and figure sizes in Matplotlib. Data visualization is a valuable tool to help you communicate your data. Being able to customize exactly how your plots are sized gives you the flexibility to produce your desired results. This allows you to produce print-ready visualizations. By the end of this tutorial, you’ll have learned: How to change the plot and figure size using measurements in inches How to set the DPI of a plot and figure How to change the size of a plot by a factor of its size Loading a… Read More »How to Change Plot and Figure Size in Matplotlib
- Implementing the Sigmoid Function in PythonIn this tutorial, you’ll learn how to implement the sigmoid activation function in Python. Because the sigmoid function is an activation function in neural networks, it’s important to understand how to implement it in Python. You’ll also learn some of the key attributes of the sigmoid function and why it’s such a useful function in deep learning. By the end of this tutorial, you’ll have learned: What the sigmoid function is and why it’s used in deep learning How to implement the sigmoid function in Python with numpy and scipy How to plot the sigmoid function in Python with Matplotlib… Read More »Implementing the Sigmoid Function in Python
- How to Add Titles to Matplotlib: Title, Subtitle, Axis TitlesIn this tutorial, you’ll learn how to add titles to your Matplotlib plots. You’ll learn how to add a title, a subtitle, and axis labels to your plot and subplots. You’ll learn how to style these titles individually and to multiple plots at once. Being able to add titles gives you the ability to better communicate what your data is saying. Matplotlib gives you incredible flexibility to better customize and tweak every element of your plots titles. By the end of this tutorial, you’ll have learned: How to add titles, subtitles, and axis titles to your plot How to style… Read More »How to Add Titles to Matplotlib: Title, Subtitle, Axis Titles
- Pandas Scatter Plot: How to Make a Scatter Plot in PandasIn this tutorial, you’ll learn how to use Pandas to make a scatter plot. Under the hood, Pandas uses Matplotlib, which can make customizing your plot a familiar experience. Pandas allows you to customize your scatter plot by changing colors, adding titles, and more. In more recent versions, Pandas included the ability to use different backends for plotting data. In this tutorial, we’ll explore the default of Matplotlib, though most of the tutorial can extend to different backends. Being able to visualize your data easily is an important step in determining where to take your analysis. In many cases, looking… Read More »Pandas Scatter Plot: How to Make a Scatter Plot in Pandas
- Plotting in Python with MatplotlibIn this tutorial, you’ll learn how to get started with plotting in Python with the matplotlib library. You’ll learn how the matplotlib library works and gain an understanding of its “anatomy”. You’ll learn how to plot and customize some simple graphs and how to use the matplotlib library with Pandas. Finally, you’ll learn how to plot and discover different plot types. Making graphs, or plots, is an incredibly important skill in your data science journey. There’s a reason people say that a picture is worth a thousand words. Whether you’re using plotting as part of your exploratory data analysis or… Read More »Plotting in Python with Matplotlib
- Matplotlib Scatter Charts – Learn all you need to knowLearn how to create Matplotlib scatter charts, including how to customize colours, add titles, change transparency and size of markers.
- Matplotlib Bar Charts – Learn all you need to knowLearn how to create Matplotlib bar charts, including how to customize bar colours, add titles, stacked and double bar charts.
- Matplotlib Line Charts – Learn all you need to knowLearn how to make Matplotlib line charts, including how to add multiple lines, customize labels, add data labels, and add a legend.
- Plotting a Histogram in Python with Matplotlib and PandasLearn what histograms are and how to create them in Python with Matplotlib and Pandas.