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Found 10784 Articles for Python
3K+ Views
Matplotlib is a popular data visualization library in Python known for its flexibility and high-quality visualizations. By following this tutorial, you will learn how to create a legend with a color box on your Matplotlib figure, making your visualizations more informative and visually appealing. Before diving into the code, it is important to understand the different elements of a legend. A legend is a key that labels the elements in our plot with different colors, markers, or lines. By adding a legend, we can understand the data being presented and make it easier for the audience to interpret our visualizations. ... Read More
2K+ Views
This tutorial will explain how to manually add the legend text size and color on a Plotly figure using Python. By the end of this tutorial, you will be able to create interactive graphs and charts with the help of the potent Python data visualization package, Plotly. Plot development must include a legend that aids viewers in comprehending the information. However, not all situations will be accommodated by Plotly's default legend settings. This article will discuss how to manually apply legend colors and font sizes to a Plotly figure in Python. Syntax Plotly's update_layout() method and the legend_font_color and legend_font_size ... Read More
262 Views
This tutorial will explain how to make Stripplot with Jitter in Altair Python. It is quick and easy to visualize a dataset containing a continuous and a categorical variable using a strip plot with jitter in Altair Python. In a strip plot, one of the variables is categorical, and the other is continuous. Strip plots are a sort of scatter plot. We can see the distribution of the continuous variable for each category by looking at the data points as individual points along the categorical axis. Spreading out the data points on the plot with jitter makes it simpler to ... Read More
157 Views
Pandas is an open-source Python library designed for data manipulation and analysis. It provides powerful data structures like Series (1-dimensional labeled array) and DataFrame (2-dimensional labeled array) that can handle different types of data and operations, such as reading and writing data from/to various file formats, merging, filtering, aggregating, and pivoting data, as well as handling missing or duplicate data. Pandas also supports time-series data and provides extensive data visualization capabilities. Its ease of use, versatility, and performance make it a popular choice among data scientists and analysts for exploratory data analysis, data cleaning, and feature engineering tasks. ... Read More
782 Views
A boxplot, also known as a box-and-whisker plot, is a graphical representation of a dataset that displays the median, quartiles, and outliers of the data. The box represents the interquartile range (IQR), which is the range between the 25th and 75th percentiles of the data. The median is shown as a line within the box. The whiskers extend from the box to show the range of the data, excluding outliers. Outliers, which are data points that fall outside of the whiskers, are typically shown as individual points or asterisks. Boxplots are useful for summarizing the distribution of a dataset and ... Read More
11K+ Views
Pandas is a powerful and popular data manipulation library in Python that provides a flexible and efficient way to handle and analyze data. One of the key features of Pandas is its DataFrame object, which is a two-dimensional tabular data structure similar to a spreadsheet or a SQL table. When printing a Pandas DataFrame directly in a Jupyter notebook or a Python console, it automatically truncates the display output when the DataFrame has many rows. By default, only a limited number of rows and columns are displayed to ensure that the output is concise and easier to read. This ... Read More
441 Views
Meteograms are graphical representations of weather data over a specific time period, typically displayed on a single plot. They provide a concise and visual way to represent multiple weather variables, such as temperature, humidity, wind speed, precipitation, etc., over time. Meteograms are widely used in meteorology and weather forecasting to analyze and visualize weather trends and changes. A typical Meteogram consists of a time axis along the x-axis, representing the time period of interest, and one or more vertical axes along the y-axis, representing the weather variables being plotted. Each weather variable is typically plotted as a line or a ... Read More
3K+ Views
Django is a Python web framework developer used to develop web applications faster and write down easy code syntax. Also, Django is a full feature rich application as it contains many features, including the Django signals. In Django, signals are used to trigger some function whenever any event occurs. For example, when users make some changes in the database, we can trigger a particular function, which can show the changes to users on the web page. The Django contains a total of 3 types of signals which we have explained below. Pre_save/post_save − It triggers the action whenever a ... Read More
5K+ Views
PyGame Pygame is a Python library used to develop games and multimedia applications. It provides functionality for handling user input, graphics, sound, and other multimedia-related tasks. Pygame is built on the SDL (Simple DirectMedia Layer) library, providing low-level access to audio, keyboard, mouse, joystick, and graphics hardware. Pygame provides a high-level interface to SDL, making it easier to use for Python developers. With Pygame, developers can create 2D games, arcade-style games, educational games, simulations, and other multimedia applications. Pygame provides a set of modules for handling graphics, audio, input, and other game-related tasks. It also includes tools for working with ... Read More
918 Views
An Area Chart is like a magician's hat of data visualization - it pulls out information about the cumulative magnitude of different variables over time or any other ordered dimension. You can see the magic happen as the chart unfolds, showing you the total magnitude of the variables in the form of stacked area plots. Each line represents a variable, and the area under it represents its magnitude at each point in time. With this chart, it's easy to compare the relative contributions of each variable to the total magnitude at any given time. If you want to dive into ... Read More