https://github.com/eslamdyab21/data-visualization-using-matplotlib-and-seaborn
This is the last project in the nanodegree udacity program. it's about data visualization.
https://github.com/eslamdyab21/data-visualization-using-matplotlib-and-seaborn
data data-analysis data-visualization matplotlib pandas python seaborn udacity udacity-data-analyst-nanodegree
Last synced: about 1 month ago
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This is the last project in the nanodegree udacity program. it's about data visualization.
- Host: GitHub
- URL: https://github.com/eslamdyab21/data-visualization-using-matplotlib-and-seaborn
- Owner: eslamdyab21
- Created: 2021-07-05T13:30:58.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2021-07-05T13:32:30.000Z (almost 5 years ago)
- Last Synced: 2025-03-15T09:42:57.905Z (over 1 year ago)
- Topics: data, data-analysis, data-visualization, matplotlib, pandas, python, seaborn, udacity, udacity-data-analyst-nanodegree
- Language: Jupyter Notebook
- Homepage:
- Size: 1.36 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
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README
# Titanic Data Exploration
## Dataset
I've choose this dataset for the visualizations Project to communicate data findings. this dataset have records of the passengers who were in the Titanic backthen,like the surviving status, siblings, classes, age, fare....
it's from kaggle and it's mainly for machine learning. but i find it very neat and will be good for the visualization purpurses of this project as i manged to get intersiting qustions.
you can find the dataset here:
https://www.kaggle.com/c/titanic/data
## Summary of Findings
In the exploration, I found that there was a strong relationship between the
survivors and their gender, female have more chances of suviving. majority of people didn't survive.
and most people were between the age of 19 and 35, and yenger people had more chances of surviving.
majority had low fare low class, and it turned out that the higher the class and the fare, the higher the chances of surviving.
majority of people traveled without family too, and it turnd out that those people had less chance of survivig
compared to travellers with family.
majority of people are with low badjet and with ages between 17 and 32
## Key Insights for Presentation
For the presentation, I start by introducing the questions, followed by the pattern in carat distribution,
then the answer.
I introduced each of the Univariate variables one by one. To start,
I use the bar and pie chart plots of survivors. then the age distribution in a violin chart.
then the fare in hist chart. then the class and siblings number then started to answer the rest of the questions by the Multivariate Relationships between varibles.