1. Air Pollution Forecasting/空气污染预测
In this tutorial, we are going to use the Air Quality dataset.
本教程中我们将使用空气质量数据集
This is a dataset that reports on the weather and the level of pollution each hour for five years at the US embassy in Beijing, China.
这是一个数据集，报告了美国在中国北京的大使馆五年每小时的天气和污染水平
The data includes the date-time, the pollution called PM2.5 concentration, and the weather information including dew point, temperature, pressure, wind direction, wind speed and the cumulative number of hours of snow and rain. The complete feature list in the raw data is as follows:
这些数据包括时间，称为PM2.5浓度的污染，和包括露珠，温度，压力，风向，风速和雨雪累积时间的天气信息，原始数据中完整的特征如下所列：
- No: row number/行号
- year: year of data in this row/年
- month: month of data in this row/月
- day: day of data in this row/日
- hour: hour of data in this row/小时
- pm2.5: PM2.5 concentration/PM2.5
- DEWP: Dew Point/露
- TEMP: Temperature/温度
- PRES: Pressure/压力
- cbwd: Combined wind direction/组合风向（大概就像东北风，西南风之类的，哈哈）
- Iws: Cumulated wind speed/累计风速（计算平均值，还是怎么的？）
- Is: Cumulated hours of snow/积雪小时
- Ir: Cumulated hours of rain/集雨小时
We can use this data and frame a forecasting problem where, given the weather conditions and pollution for prior hours, we forecast the pollution at the next hour.
我们可以用这个数据，构建一个预测问题，给出前几小时的天气状况和污染（PM2.5），我们预测接下来几个小时的污染(PM2.5)
This dataset can be used to frame other forecasting problems.
这个数据集可以用来构建别的预测问题（估计意思是除了PM2.5之外的其他预测，如集雨，积雪小时等）
Do you have good ideas? Let me know in the comments below.
你有好主意吗？请在下面的评论中告诉我
You can download the dataset from the UCI Machine Learning Repository.
您可以从UCI Machine Learning Repository下载数据集。
Download the dataset and place it in your current working directory with the filename “raw.csv“.
下载数据集并将其放在当前工作目录中，文件名为“raw.csv”。