Column operations
As we have now known Pandas dataframe loading and slicing, it is time to move on to actions! There is a sayings that goes "if you don't love data at…
Pandas DataFrame
In the previous post, we have learned how to import data from several different formats into Python for analysis. One similarity among those data-loading functions is that they all generate…
Loading Data with Pandas
NumPy is a very powerful library for numerical manipulations. However, to some extends, NumPy is fairly "low level" in that writing codes with it is not that "friendly" to data…
Array Concatenation
Now that we have known how a fair bit about NumPy array basics and operations, let us discuss another important operation - array concatenation. In short, concatenation means to join…
NumPy Operations
Previously, we have talked about creating and slicing NumPy arrays. Now, let us see what else we can do with them. In short, a lot! The library has a huge…
NumPy Arrays
The first tool we will be learning in the data science stack in Python is NumPy arrays. NumPy is a Python package for numerical manipulations. It comes with powerful features…
Descriptive Statistics
I do not fully agree with the saying "the end justifies the mean". The sum also justifies the mean, not just the n... Yes, it is a dad joke when…
Data Analytics Critical Applications
This is a presentation that summarized my research until 2019. I majorly designed advanced data analytics models for critical applications like cyber security and fintech.
Predictive Analysis
As we discussed in the last post, predictive analysis is a family of analysis that aims to learn useful knowledge from data collected historically. The learned knowledge is then applied…
Data Analysis Types
Now that we have established the concept of tabular data, let discuss what we can do with them. The goal of data science is to discover useful knowledge from mountains…