We will be using Congressional Voting Records Data Set from UCI Machine Learning Repository (download data). This data set includes votes for each of the U.S. House of Representatives Congressmen on the 16 key votes identified by the CQA. The target variable will be the Class Name (either Republican or Democrat) in the data set. We will be applying the k-Nearest Neighbors Classification Algorithm to predict the party affiliation of United States congressmen on their voting records.

The structure of our project will be as follows —

  • Importing the necessary libraries.
  • Loading the data set.
  • Knowing the data.
  • To perform…

In this project, we’ll be using Credit Card Approval Dataset from UCI Machine Learning Repository. The structure of our project will be as follows —

  • To get a basic introduction of our project & What’s the business problem associated with it ?
  • We’ll start by loading and viewing the dataset.
  • To manipulate data, if there are any missing entries in the dataset.
  • To perform exploratory data analysis (EDA) on our dataset.
  • To pre-process data before applying machine learning model to the dataset.
  • To apply machine learning model that can predict if an individual’s application for a credit card will be…

In this Article, we will learn how can we perform some more image processing algorithms in Python language.

For Introduction to Image Processing in Python, What is Image Processing, How to install OpenCV on your system, you can refer to my article-

Geometric Transformations of Images using OpenCV|Image Processing Part-1

Let’s start using OpenCV Library-

1. Importing the required libraries:

cv2- For OpenCV (Used for Image Processing)

matplotlib- For Matplotlib (Used fot Plotting and Visualization)

numpy- For Numpy (Used for Scientific Computing)

pandas- For Pandas (Used for Data Analysis)

In this Article, we will learn how can we perform geometric transformations algorithms on images using OpenCV in Python language.

We will start off by talking a little about Image Processing, then we will move on to see different applications/ scenarios where image processing can come in handy. So, let’s begin!

What is Image Processing ?

It is important to know what exactly image processing is and what is its role in the bigger picture before diving into its how’s. Image Processing is most commonly termed as ‘Digital Image Processing’ and the domain in which it is frequently used is ‘Computer Vision’.

Both Image Processing…

Types of Merging DataFrame in Python

In this article, you’ll learn how multiple DataFrames could be merged in python using Pandas library.


Merging DataFrames is the core process to start with data analysis and machine learning tasks. It is one of the tool-kits which every Data Analyst or Data Scientist should master because in almost all the cases data comes from multiple source and files. You may need to bring all the data in one place by some sort of join logic and then start your analysis.

People who work with SQL like query languages might know the importance of this task. Pandas has full-featured, high…

Seaborn is a wonderful visualization library provided by python. It has several kinds of plots through which it provides the amazing visualization capabilities. Some of them include count plot, scatter plot, pair plots, regression plots, matrix plots and much more. This article deals with the regression plots and matrix plots in seaborn.

What are Regression Plots?

The regression plots in Seaborn library of Python are primarily intended to add a visual guide that helps to emphasize patterns in a dataset during exploratory data analysis. As the name suggests Regression plots, creates a regression line between 2 parameters and helps to visualize their linear relationships.

Getting started with Regression Plots -

1. Importing the required libraries

Categorical Data

  • Data which takes on a limited and fixed number of values.
  • Normally combined with numeric data
  • Examples include:
  1. Geography (country, state, region)
  2. Gender
  3. Ethinicity
  4. Blood type
  5. Eye color

Plot types

  • show each observations includes stripplot and swarmplot.
  • show abstract representations includes boxplot, violenplot and lvplot (also known as boxenplot).
  • show statistical estimates includes barplot, countplot and pointplot.

Let’s start visualizing using Seaborn

1. Importing the required libraries

Visualizing statistical relationships

Statistical analysis is a process of understanding how variables in a dataset relate to each other and how those relationships depend on other variables. Visualization can be a core component of this process because, when data are visualized properly, the human visual system can see trends and patterns that indicate a relationship.

In this article, we will discuss about the relplot() function of Seaborn library. This is a figure-level function for visualizing statistical relationships using two common approaches: scatter plots and line plots.

Scatter Plots- Each plot point is an independent observation

Line Plots- Each plot point…

What is Seaborn library ?

Seaborn is a data visualization library of Python similar to other visualization libraries like Matplotlib and Plotly. It is based on Matplotlib library. Seaborn is a powerful Python library that makes it easy to create informative and attractive visualizations.

Advantages of Seaborn library:

  • Easy to use
  • Works well with pandas data structures
  • Built on top of matplotlib

How to install Seaborn library?

To install the Python Seaborn library, you can use the following commands based on the platform you use:

pip install seaborn


conda install seaborn

Getting Started with Categorical Plots -

What is Categorical data?

Categorical data is a collection of information that is divided into groups i.e, if an organisation or agency is trying to get…

Ravjot Singh

A Tech enthusiast || Dedicated and hardworking with a passion for Data Science || Undergrad || Codes in Python & R.

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