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…
Functions in Python
In my post about print(), we briefly mentioned built-in functions which are named prewritten codes that we use do certain tasks multiple times. Besides print(), there are many other useful…
Collections in Python
A collection is not a strange concept. It is just a bunch of objects put together for a certain reason. You may have a collection of pictures, songs, books, movies,…
Loops in Python
Have you ever challenged yourself while exercising like "I will run 10 rounds of this park" or "I will run as many rounds as I can"? If yes, basically, you…