In this article, I am going to cover the following points:

Brief Introduction

This is a part of milestone project I have done, it was related to healthcare business which included multiple questions were answered.

In this part, I am going to explain step by step with more details how can analyze regular texts were taken from a healthcare system specifically an emergency data by using python.

In the beginning, I would like to define a regular text.

What do I mean by the regular text in this data?

It is any…


In this article, I am going to explaining in more details how could you create a dashboard in excel?

This is a screen shot of data which I will create a dashboard based on it.


Stacked Bar Chart is a Bar Chart with subcategories for each bar.

Let us take an example to explain that with more details. This is the head of data frame, the first ten rows.


Business Understanding is an essential matter and primary stage in data science lifecycle so that, all next stages form based on our Business understanding.

In shadow of technological development that world is witnessing, our business requires an innovate solutions.

Sometimes traditional formulas do not give us an accurate solution for current our issues and as simply that returns to timing of formulas created and nature of issues in that time.

let’s take a look for a real example I faced in my first contract.

In summer, Temperature degrees were raising in medical laboratories and that impacts on devices performance and…


Visualizing Important Features from Titanic dataset
Visualizing Important Features (Titanic dataset)

It’s an amazing way to see all data features in one graph. It gives us a clear picture about feature values. In this article, I’m going showing you an easy and a wonderful way to visualize data features whether categorical or numerical.

I will use Titanic dataset as an example to explore that.

First of all, we import essential libraries numpy, pandas, matplotlib and seaborn.

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

Then, reading data

df = pd.read_csv(‘train.csv’)

After that, take look for heading and show the shape of data.

df.head()

Abdulaziz Alsulami

A self Learner interested for AI & Python, love reading, write his thoughts to his own way and like presenting knowledge to world in picture which he like.

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