DEV Community: Frankline Kibet

LEARNING PYTHON

Frankline Kibet — Fri, 18 Sep 2026 06:57:26 +0000

When started this journey in tech there were a lot of noises saying python is the easiest programing language this played a very crucial role in my interest in learning python, not saying that I wanted things easily is because at that time academic pressure was killing me. After I started learning it I noticed the noises were wrong PYTHON IS NOT THE EASIEST PROGRAMING LANAGUAGE infact I think they meant powerful.

Fast-forward I developed a habit of leaning it everyday to understand all the nitty gritty of python
Here is what I learned from in a systematic way :

Variables

This is just a name that points to a value.

example
age =26
name = "Frankline"

*Data type
*

a data type classification that defines the category of a value, determining how the computer stores that data and what kinds of operations can be performed on it.

type of data type

1.Integer - whole numbers

total_bookings = 285

2.Float - decimal numbers

average_amount = 31688.42

3.String - text, in single or double quotes

name = "Alice Mwangi"

4.Boolean - True or False

is>18= False

5.List - an ordered, changeable collection

scores = [78, 85, 91, 65, 72]

6. Dictionary - key-value pairs

booking = {"booking_id": "BK0001", "room_type": "Deluxe", "total_amount": 25000}

if you want to print the output you use
print()
example
print(name),
print(is>18)

INPUT AND OUTPUT
INPUT
Pauses your program and waits for the user to type something whatever they type comes back as a string, even if it looks like a number.

this demonstrate how input works plus the output when you print ()

The f-string

the f-string is a way to insert variables directly into print
example

WINDOW FUNCTIONS

Frankline Kibet — Thu, 17 Sep 2026 17:50:12 +0000

Window function performs a calculation across a set of rows related to the current row The result is calculated per row, but the calculation itself can look at other rows around it.

Window function has over() which turns a normal aggregate function into a window function.

in this example you are able to see the average total amount compared to each room type .

determines the sequence rows are processed in for that window — essential for ranking functions and for anything

_Partition by _

It is usually written inside the over and is used to group data to the thing that you what it be grouped. It just like the group by clause but this one is for window function only, this helps that each group gets its own independent calculation.

order by

determines the sequence rows are processed in for that window essential for ranking functions and for anything
also written inside over()

ROW_NUMBER, RANK_NUMBER,DENSE_RANK,LAG,LEAD,

Row_number
This is just a simple count of row . I have used it multiple
time when the primary key is not in particular order.
Example

RANK AND DENSE RANK
Rank
The rank()function assigns a rank to each row based on the ORDER BY clause in the OVER statement. Rows with the same value receive the same rank, with gaps in the ranking for duplicate values.

TASK:see which jobrole has the highest daiyrate

Dense rank
The DENSE_RANK() function assigns ranks like RANK(), but it doesn’t skip ranks after ties

Conclusion
SQL window functions like ROW_NUMBER(), RANK(), DENSE_RANK(), NTILE(), LEAD(), and LAG() provide powerful ways to analyze data by performing calculations across rows within a defined window.

SUBQUERIES AND CTE

Frankline Kibet — Thu, 17 Sep 2026 03:30:50 +0000

Subqueries this are queries inside another query. Many of the times a problem cant be solved using a single query now thus where subqueries comes in .

Subqueries can appear in a few different places ;

Subquery inside a where clause.

example of use case

subquery on select clause used a computed column when used in the select clause.

3.Subquery on the from
this is treated as a temporary table.
example

CTE
CTE is an abbreviation for Common Table Expression it typically does everything that a subquery can do but in a more presentable way.
Most of the time I have used cte rather than a subquery .
how you write a cte is you use a with clause to define it then followed by () after that you call it like just a table but it should be immediately after writing it
example of cte

You can also have mulitple CTE
EXAMPLE

When to Use Each

Use a subquery when:

You need a quick calculated value
The logic is simple enough to read in a single nested line
You're only using that intermediate result once

Use a CTE when:

The query has multiple steps that build on each other
You want to reference the same intermediate result more than once
You're working with recursive data
Readability matters CTEs make complex queries much easier for someone else to follow especially when you are working in a large organization .

SQL JOINS WITH EXAMPLES OF EACH

Frankline Kibet — Wed, 16 Sep 2026 03:07:38 +0000

A join combines rows from two or more tables based on a related column between them. Instead of running separate queries and manually matching up results yourself, a join does that matching for you, in a single query
When working with databases, your data is often stored in more than one table. This is way join are important

*TYPES OF JOINS *

1.** Inner join**
This is a type of join that returns only the rows that have a match in both tables.
example

Left jOIN

Returns all rows from the left table plus matching rows from the right table.

Where there's no match the right table's columns come back as null

3*_.Right join _*
Returns all rows from the right table plus matching rows from the left.

4._ Full outer join _

Return all row from all table.

I used it when when you need a complete view of the table example like in this scenario above I need to check the results table and the subject table to identify areas of improvement.

_self join _

This is a practical
use of self join that really help be in my project. it let me pair each book with it author with ease.

DDL and DML WHAT ARE THEY?

Frankline Kibet — Mon, 14 Sep 2026 12:33:56 +0000

DDL
DDL is an abbreviation for data definition language used to define, modify, and manage the structure of a database.
Common DDL commands
Create - Creates a new table, database, index, or view
Example

Alter
Used to modify the exiting table
Alter can be used to:

Remove column
Add column

Truncate – it empties all rows from a table but keeps its structure

truncate table safari.student;

DML
DML is an abbreviation for data manipulation language,
These are the commands that work with the actual data stored inside tables exmple adding rows, reading rows, updating values, and deleting rows.
Example of commands
Select reads data from one or more tables
Example:

2.Insert
Adds new rows to a table

Update Is used to modifies existing rows. example

Delete is used to removes rows from a table

Diffence
The main difference: DDL defines and changes the structure of a table using commands like CREATE, ALTER, DROP while DML works with the actual data inside that structure commands like SELECT, INSERT, UPDATE, DELETE.

ANALYZING HOTEL BOOKING DATA: A TEMBO HOTEL SQL + POWER BI CASE STUDY

Frankline Kibet — Mon, 14 Sep 2026 04:29:45 +0000

Tembo Hotel had been tracking all of their bookings in Excel, but the data had grown messy over time inconsistent formatting, duplicate entries, and mixed date formats made it impossible to get reliable answers out of it. I was tasked with cleaning the dataset and turning it into something the CEO could actually use to understand the business.

Here's how I approached it, from raw CSV to a working Power BI dashboard.

The cleaning process started by deleting duplicates .

Then standardization values and trimming to remove extra space.

the changing the data format and data type from text to data

after the cleaning process is over I loaded the clean data on table which I will use for analysis.

The CEO wanted to know about his business . Analysis started by answering major business questions
ANALYSIS

Revenue analysis

Guest insighs
staff performance

Cancellation and revenue lost

One of the more important findings: a meaningful share of potential revenue was lost specifically to cancellations, concentrated in certain room types more than others.

I created it as view so that it so that it could be easy to import then on power bi for visulation

Presenting the outcome

Dashboard 2.The revenue analysis
Guest insight

cancelation and revenue lost on it .

REPORT

Data

Frankline Kibet — Mon, 07 Sep 2026 11:58:42 +0000