In this section, we are going to play with data we cleaned in the last section to derive some insightful information.
Exploratory Data Analysis is the critical process of performing initial investigations on data so as to discover patterns,to spot anomalies,to test hypothesis and to check assumptions with the help of summary statistics and graphical representations.
Data cleaning and preparation is the most critical first step in any AI project. As evidence shows, most data scientists spend most of their time up to 70% on cleaning data. In this blog post, I’ll guide you through these initial steps of data cleaning and preprocessing in Python.
The datasets are linked at the bottom
The first step one needs to do is importing the required libraries. There are lots of libraries available, but the most popular and important Python libraries for data cleaning and analysis purposes are Numpy and Pandas.
import pandas as pd
import numpy as np
I came to know that our college (GEC THRISSUR)was one among the 14 colleges in Kerala which was selected to start the DSC(Developer students club)an initiative by GOOGLE and i also heard that the club is conducting an Android workshop,I was not that interested about the workshop as i had a previous experience of an Android workshop which did’nt turn out really well.
A few days after that my friends told me that the workshop was not just about the Android development that Felix Josemon(he is our senior who led the DSC club in our college and was one among…
In the bleak midwinter