The Sun is an extremely powerful energy source, and the sunlight is by far the largest source of energy received by Earth, but its intensity at Earth’s surface is quite low. This is essential because of the enormous radial spreading of radiation from the distant Sun. With energy costs and consumption rising dramatically, the need for renewable energy has become urgent. In line with the Kingdom’s Vision 2030 plan to diversify energy sources. This project goal is to predict the weather in Saudi Arabia especially Sunny or Not sunny, to use for solar energy Where are the best location and the best days to work.
It would be interesting to see any machine learning techniques or continued data visualizations applied to this data set.
What are the best cities in Saudi Arabian for do Solar Energy?
| Field Name | Description |
|---|---|
| City | KSA city name |
| Date | recorded date |
| Time | recorded time |
| Year | recorded date - year |
| Month | recorded date - month |
| Day | recorded date - day |
| Hour | recorded time - hour |
| Minute | recorded time - minute |
| Weather | recorded weather description ( clear - sunny - Sunny - Cloudy - Rainy - Windy ) |
| Temp | a meteorological code for upper air soundings |
| Wind | wind speed |
| Humidity | umidity is the amount of water vapor in the air |
| Barometer | used to measure air pressure in a certain environment |
| visibility | the quality or state of being visible, the degree of clearness |
- pandas
- numpy
- seaborn
- plotly.express
- matplotlib.pyplot
- pandas_profiling
- sklearn.model_selection
- sklearn.linear_model
- sklearn.preprocessing
- sklearn.metrics
- sklearn.metrics
- sklearn.ensemble
- sklearn import datasets
- sklearn.neighbors
- sklearn.datasets
- sklearn.tree
- sklearn.ensemble
- ipywidgets
- imblearn.over_sampling
- imblearn.under_sampling
- mlxtend.classifier
- collections
- wordcloud
- xgboost
- warnings
- python
- jupyter notebook
- PowerPoint