Base64 encoding is used to convert binary data into a text format. This is useful for transferring data over the internet, encoding binary files, storing data in text formats, etc. In this article, we will understand what Base64 encoding is and see how we can encode binary data along with decoding in Node.js. Why We […]
How to Encode and Decode Base64 Strings in Node.js Read More »
Recently I was working on a large Node.js project having a huge number of libraries installed and since the project is on a production server, it is quite difficult for me to see the libraries my team installed. Due to reasons like errors or compatibility issues, we also want to see the version of a
How to Get a List of Installed NPM Packages (Multiple Methods) Read More »
NumPy is a famous Python library used to perform various types of mathematical operations on elements of multi-dimensional arrays. It is a fundamental package when it comes to scientific computing with Python. In this article, we’ll look at three ways of inverting elements of a boolean array with NumPy along with some examples for better
How to Invert the Elements of a Boolean Array in Python (3 Methods) Read More »
Images are an integral part of our surroundings, and having the ability to manipulate them or transform their appearance is a valuable skill. Image processing finds its application in a wide range of fields, including data visualization and machine learning, where automated systems handle thousands of images simultaneously. In this article, we will look into
Convert RGB Images to Grayscale Using Matplotlib: A Step-by-Step Guide Read More »
DataFrames are a well-known data structure provided by Python‘s Pandas library. They can be used to store data in a two-dimensional tabular form, which is convenient for visualizing and manipulating various types of data. Since DataFrames are 2D, they contain rows and columns. In this article, we’re going to look at 3 distinct methods of
Getting Number of Rows and Columns in Pandas DataFrame (3 Methods) Read More »
Pandas is a data analysis and manipulation library in Python that allows the user to read and work with different types of data. In order to store and manipulate data, Pandas uses DataFrames. DataFrames in pandas are two-dimensional mutable tabular structures, containing rows and columns much like a spreadsheet. In this article, we will be
Replace Multiple Values in a DataFrame Using Pandas Read More »
Python‘s Pandas library is well known for its ability to store and retrieve data efficiently. With the help of DataFrames, Pandas makes data visualization and manipulation easy as well. In this article, we’ll look at one of Pandas’ crucial functions, query() which allows us to filter and display certain records from the DataFrame according to
Pandas query() Method: Querying DataFrame in Python Read More »
Pandas is a popular data manipulation library in Python that helps us work with various types of datasets. Pandas provides DataFrames, a two-dimensional tabular structure containing rows and columns that help us store said datasets. In many cases, we may have more than one DataFrame in our program which needs to be combined. Pandas provides
Appending Dataframes in Pandas (Multiple Examples) Read More »
CSV (Comma Separated Values) is a plain text file format used to store tabular data, commonly in spreadsheets. In a CSV file, every line represents a record and each field in that line of record is separated using a comma. We mainly use CSV to import and export data between applications. Python provides us with
Reading and Writing CSV Files in Python Read More »
Matplotlib is a well-used tool by many developers when it comes to data visualization using graphical plots. It can also be used to generate plots for datasets created using Python libraries such as NumPy and Pandas. However, when it comes to plotting multiple datasets, a scatterplot is the way to go. A scatterplot helps us
Plotting Multiple Datasets on a Scatterplot Using Matplotlib Read More »