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Articles by Niharika Aitam
Page 13 of 14
Django form field custom widgets
A widget is the representation of the Html input element using Django. The widget is used to handle the rendering of the HTML page and data extracting from the POST/GET dictionary. Every time whenever we specify the field on a form, Django uses the default widget to display the data in an appropriate manner. Django is the one of the best Framework used by most of the users, to perform the web development. It provides many advanced features, functions and packages to design the best web pages and connect with the servers using the python programming language. Now let’s ...
Read MoreDjango Form submission without Page Reload
In Django, we can submit the form without reloading the page using the Jquery and Ajax (Asynchronous JavaScript and XML) requests. Let’s see an example to work with the Ajax to submit the Django form without reloading the page. Create a new Django project First create a new project in Django with the name Reload_project and also create a new app in the project directory with the name Reloadapp by executing the below commands in the command prompt. django-admin startproject Reload_project cd Reload_project django-admin startapp Reloadapp Now in INCLUDED_APPS in settings.py file of the Reload_project directory, add the ...
Read MoreDivide each row by a vector element using NumPy
We can divide each row of the Numpy array by a vector element. The vector element can be a single element, multiple elements or an array. After dividing the row of an array by a vector to generate the required functionality, we use the divisor (/) operator. The division of the rows can be into 1−d or 2−d or multiple arrays. There are different ways to perform the division of each row by a vector element. Let’s see each way in detail. Using broadcasting using divide() function Using apply_along_axis() function Using broadcasting Broadcasting is the method available ...
Read MoreDifferent Types of Joins in Pandas
Pandas is one of the popular libraries used to perform data analysis and data manipulation. There are many advanced features to work with the tabular data such as join multiple data frames into one depending upon the common columns or indices of columns. In python, there are different types of joins available which can be performed by using the merge() function along with the how parameter of the pandas library. Following are the different joins. Inner Join Outer Join Left Join Right Join Cross Join Inner Join An Inner Join in the pandas library will return the rows ...
Read MoreHow to check if something is a RDD or a DataFrame in PySpark?
RDD is abbreviated as Resilient Distributed Dataset, which is PySpark fundamental abstraction (Immutable collection of objects). The RDD’s are the primary building blocks of the PySpark. They split into smaller chunks and distributed among the nodes in a cluster. It supports the operations of transformations and actions. Dataframe in PySpark DataFrame is a two dimensional labeled data structure in python. It is used for data manipulation and data analysis. It accepts different datatypes such as integer, float, strings etc. The column labels are unique, while the rows are labeled with a unique index value that facilitates accessing specific rows. ...
Read MoreWhat are the seaborn compatible IDLEs?
Integrated Development Environments (IDEs) are software applications that provide comprehensive tools and features to facilitate software development. The following are the IDLEs that are compatible with seaborn library. Jupyter Notebook/JupyterLab Jupyter Notebook and JupyterLab are widely used interactive computing environments for data analysis and visualization. They provide a web-based interface where we can write and execute Python code in cells. Seaborn integrates seamlessly with Jupyter Notebook and JupyterLab, allowing us to create and visualize plots directly within the notebook environment. The inline plotting feature in Jupyter Notebook displays Seaborn plots directly in the notebook, making it easy to iterate on ...
Read MoreWhich way the pandas data can be visualized using seaborn?
Seaborn offers various ways to visualize pandas data, allowing you to gain insights and communicate patterns or relationships effectively. Here are some common ways to visualize pandas data using Seaborn. Scatter Plots The `scatterplot()` function can be used to create scatter plots that show the relationship between two numeric variables. You can use Seaborn to enhance the scatter plot with additional visual cues, such as color-coding points based on a categorical variable using the `hue` parameter. Line Plots The `lineplot()` function can be used to create line plots to represent trends or changes over time or any other continuous numeric ...
Read MoreWhat are the main components of a Seaborn plot?
A Seaborn plot consists of several main components that work together to create informative and visually appealing visualizations. Understanding these components can help you customize and interpret Seaborn plots effectively. The below are the main components of a Seaborn plot. Figure and Axes Seaborn plots are created using Matplotlib's figure and axes framework. The figure represents the entire canvas or window on which the plot is displayed. The axes represent the individual subplots or regions within the figure where the actual data is plotted. Seaborn functions typically create a figure with a single set of axes by default, but you ...
Read MoreConvert a NumPy array to an image
The array created using the Numpy library can be converted into an image using the PIL or opencv libraries in python programming language. Let’s see about each library one by one. Python Image Library PIL is abbreviated as Python Image Library, which is an image processing libraries in python. It is a light weight and easy to use library to perform the image processing tasks like reading, writing, resizing and cropping the images. This library performs all the basic image processing tasks but don’t have any advanced features required for computer vision applications. We have a function in ...
Read MoreConvert a NumPy array into a csv file
The Numpy is the library in the python programming language which is abbreviated as Numerical Python. It is used to do the mathematical, scientific and statistical calculations within less time. The output of the numpy functions will be an array. An array created by the numpy functions can be stored in the CSV file using a function namely, savetxt(). Numpy array into a .csv file CSV is abbreviated as Comma Separated Values. This is the file format most widely used in the Data Science. This stores the data in a tabular format where the column holds the data fields and ...
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