Here in this post, we will see how we can read most common file formats used in Data Science (using Python) with code. When you are working as a Data Scientist or Data Analyst, your most of the time is utilized in reading the dataset from different sources (including data saved in different file formats and […]

## Handling missing values using Python in Data Science

When you start your journey towards data science or data analysis, one thing is for sure that the major task in both these positions is of handling missing values using Python or R whatever platform or language you choose. It’s said that almost 75 – 80% of the time, a data scientist or data analyst […]

## 10 Basic Python fundamentals for Data Scientist aspirants and Data Analysis

When you want to learn Data Science or Data Analysis, you have to learn either Python or R and after that using basic python/R functions with other statistical packages you can easily start analysing data and get some insight from your data. As i too have both the options, i chose Python over R as […]

## Computing Bootstrap Replicate from Bootstrap Sample using Python

The basic idea is that instead of literally repeating the data acquisition process over and over again, we can simulate those repeated measurements using python. Here in this post, we will see how you can compute Bootstrap replicate from a bootstrap sample using Python Statistical Inference It is defined as a process by which we […]

## Anscombe Quartet and use of Exploratory Data Analysis

Whether you are working as Data Scientist or looking to build a career in a Data Science, the pipeline of your work include Extracting dataset, loading dataset, Data Cleansing and munging, finding summary statistics, then do some Exploratory Data analysis (EDA), and after all these things build a model using machine learning. Anscombe Quartet dataset demonstration […]

## Performing Linear Regression using Least Squares

Linear regression is defined as a linear approach which is used to model the relationship between dependent variable and one or more independent variable(s). When we try to model the relationship between a single feature variable and a single target variable, it is called simple linear regression. But when there is more than one independent […]