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Articles by Niharika Aitam
Page 11 of 14
Comparing and Managing Names Using name-tools module in Python
The name-tools module is a python library which provides us the tools to work with the names. These are used in many applications likely data cleaning, text processing and Natural Language Processing etc. It has a several functions for comparing and managing the names. Installing name-tools Before working with the name-tools, we need to install it in the python environment. The following is the process for installing the name-tools. pip install name-tools After executing the above code, if you see the text below, then the installation is considered successful. Collecting name-toolsNote: you may need to restart the kernel ...
Read MoreHow to remove axes spine from the plot in seaborn?
The axes spines, also known as the axis lines, which are the lines that define the borders or boundaries of a plot's coordinate system. In a two-dimensional plot, there are typically four axes spines such as top, bottom, left, and right. These spines create the framework for the plot and serve as reference lines for the data points. Each spine represents one of the four sides of the plot. The top spine runs horizontally across the top, the bottom spine runs horizontally across the bottom, the left spine runs vertically along the left side, and the right spine runs vertically ...
Read MoreCMY and CMYK Color Models using Python
The CMY and CMYK color models are subtractive color models used in printing and graphic design. In Python, we can work with these color models using various libraries and tools. Let's see each color model in detail. CMY color model The CMY color model, also known as the subtractive color model, which is a system used for mixing colors in various applications like printing, painting, and graphic design. CMY stands for Cyan, Magenta, and Yellow, which are the primary colors in this model. In the CMY color model, colors are created by subtracting different amounts of cyan, magenta, and yellow ...
Read MoreHow to change the figure style to Ticks in Seaborn?
In Seaborn, the "ticks" figure style is a minimalistic style that removes the background grid lines but retains the tick marks on the axes. This style focuses on presenting the data without any distracting elements and is useful when we want a clean and simple look for our plots. When we set the figure style to "ticks" in Seaborn using the 'sns.set_style()' function, the following changes occur in our plots. Background Grid Lines − The background grid lines are removed, resulting in a blank canvas without any horizontal or vertical lines. This helps to reduce visual clutter and draw ...
Read MoreWhat is the way to convert the figure style to Whitegrid in Seaborn?
Seaborn is a popular data visualization library in Python that provides a variety of styles to enhance the visual appearance of plots. One of the available styles is "whitegrid, " which offers a white background with grid lines. Changing the figure style in Seaborn is a straightforward process, and it can greatly impact the aesthetics of our visualizations. In this article we are going to see how to change the figure style to white Grid in seaborn. To change the figure style to "whitegrid" in Seaborn, we can follow below steps. Install Seaborn First we should check if we have ...
Read MoreHow to change the figure style to Darkgrid in Seaborn?
Seaborn provides several built-in figure styles that we can choose from to enhance the visual appearance of our plots. These styles affect various elements such as colors, grid lines, background, and fonts. To set the figure style in Seaborn, we can use the sns.set_style() function. The following are the available figure styles in Seaborn library. Darkgrid − This style features a dark gray background with grid lines, which helps in focusing attention on the data points. Whitegrid − This style is similar to "darkgrid" but with a white background, making it suitable for plots with lighter color schemes. Dark ...
Read MoreFinding the Common items among Python dictionaries
A Dictionary is one of the unordered data structures available in python to store the data in the key and value pair. It is also known as Associative array or Hash map in other programming languages. The dictionary is represented using the curly braces {} and the key and value are separated using a colon “:” The keys in the dictionary are unique and the values can be of duplicates. To access the elements of the dictionary we will use the keys. Example The following is the example of creating a dictionary using the dic() method and curly braces {} available ...
Read MoreWhat is the purpose of White figure style in seaborn?
The "white" figure style in Seaborn is a predefined style that provides a clean and minimalistic appearance to our plots. It is designed to enhance the visual clarity of the plot elements and prioritize the data representation. The purpose of the white figure style is to create visually appealing and easy-to-read plots by emphasizing the data while reducing distractions. Here are the key aspects and benefits of using the "white" figure style in Seaborn. Background Color The white figure style sets the background color of the plot to white, which creates a neutral and unobtrusive background. This helps to draw ...
Read MoreCan Seaborn be used to perform calculations on data, such mean or standard deviation?
Seaborn is primarily a data visualization library and does not provide direct methods for performing calculations on data, such as calculating mean or standard deviation. However, Seaborn works seamlessly with the pandas library, which is a powerful data manipulation library in Python. You can use pandas to perform calculations on your data, and then use Seaborn to visualize the calculated results. The mean is a statistical measure that represents the average value of a set of numbers. It is calculated by summing up all the numbers in the set and then dividing the sum by the total count of numbers. ...
Read MoreHow is Seaborn used to group the data by one or more columns?
Seaborn is primarily a data visualization library and does not provide direct methods for grouping data by one or more columns. However, Seaborn works seamlessly with the pandas library, which is a powerful data manipulation library in Python. We can use pandas to group our data by one or more columns, and then use Seaborn to visualize the grouped data. By combining the data manipulation capabilities of pandas to group our data by one or more columns with the visualization capabilities of Seaborn, we can gain insights from our data and effectively communicate our findings through visualizations. Here's a detailed ...
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