DATA-INSIGHTS(PART 3): PYTHON EDA(VISUALIZATION) VS MICROSOFT POWER BI
- INTRODUCTION
Dataset description: Hotel booking demand; This data set contains booking information for a city hotel and a resort hotel, and includes information such as when the booking was made, length of stay, the number of adults, children, and/or babies, and the number of available parking spaces, among other things.
Download Dataset: https://www.kaggle.com/jessemostipak/hotel-booking-demand
GOAL : This project compares Python Pandas Exploratory Data Analysis (EDA)Visualization(using barcharts) and Microsoft PowerBI to determine ease of use and have some data insights. We answer some questions about the dataset to get data insights.
Concepts learnt:
Pivot tables
bar charts ploting
pivot tables (operations)
Powerbi Dashboard.
2. PYTHON EDA VISUALIZATION
Using python pandas,pivot-table,we will use visualizations to answer some questions and get data insights.
2.1 import libraries and view dataset
QUESTIONS
2.2 Compare adults and number of meals?
2.3 in what country is the total of special request the highest for transient customer type?
2.4 Number of adults that had no deposit in each month?
2.5 Number of required parking spaces in july? and number of agents from Norway?
3 MICROSOFT POWERBI DASHBOARD VISUALIZATION
Using PowerBi we plot some visualization to answer same questions.
PowerBI Dashboard Link: https://app.powerbi.com/groups/me/reports/b9c35fed-b2ad-46bc-8a43-f528a7bbf850?ctid=f83c47c9-f7ff-47a2-8c3b-c986af680622
3.1 Compare adults and number of meals?
3.2 in what country is the total of special request the highest for transient customer type?
3.3 Number of adults that had no deposit in each month?
3.4 Number of required parking spaces in july? and number of agents from Norway?
4 CONCLUSION
For this visualization , PowerBI Is faster and easier to use, however using python gives you flexibility.
WRITER: OLUYEDE SEGUN . A(jnr)
PowerBI Dashboard Link: https://app.powerbi.com/groups/me/reports/b9c35fed-b2ad-46bc-8a43-f528a7bbf850?ctid=f83c47c9-f7ff-47a2-8c3b-c986af680622
Explanatory Notebook and dataset:
https://github.com/juniorboycoder/PYTHON_EDA_VISUALIZATION
linkelin profile: https://www.linkedin.com/in/oluyede-segun-jr-a-a5550b167/
twitter profile: https://twitter.com/oluyedejun1
TAGS: #POWERBI #DATASCIENCE #DATAVISUALIZATION #EDA #PYTHON #PANDAS
