Have you been curious to know which cars are most popular in US and what are their typical rental fares in various cities? As the head of Product and Data Science at an emerging technology start-up, Ving Rides, these were some of the questions I was trying to answer. I gathered lot of insights through this exercise, but for the sake of time I will be presenting some of the most interesting ones for your consumption.

您是否想知道哪种汽车在美国最受欢迎，在各个城市的典型租金是多少？ 作为新兴技术创业公司Ving Rides的产品和数据科学负责人，这些是我要回答的一些问题。 通过此练习，我收集了很多见解，但是为了节省时间，我将介绍一些最有趣的见解供您使用。

Read on to know these answers presented using some beautiful visualizations.

继续阅读，以了解使用一些精美的可视化呈现的答案。

见解： (The Insights:)

I’ll list some caveats and other details later, but first let’s dive straight into the findings from this exploration:

稍后我将列出一些注意事项和其他细节，但首先让我们直接了解一下本次探索的结果：

1. Tesla is the most rented car:

1.特斯拉是租金最高的汽车：

Closely following Tesla is Toyota, BMW, Ford and Chevrolet. Below figure shows the make of cars against daily rental values and is arranged from top to bottom in the order their counts/numbers i.e. popularity. Each dot below represents a car from the dataset!

紧随特斯拉之后的是丰田，宝马，福特和雪佛兰。 下图显示了按日租金计算的汽车制造商，并按其数量/数量(即受欢迎程度)从上到下排列。 下面的每个点代表数据集中的一辆汽车！

2. Rarest Cars are: McLaren, Saab, Suzuki, Mercury and Genesis

2. 稀有汽车有：迈凯轮，萨博，铃木，水星和创世纪

These results can be seen in the previous figure.

这些结果可以在上图中看到。

3. Majority of Car rental fare is between 35–60 Dollar per day range

3.大多数租车费每天在35–60美元之间

2. Most expensive cities for car rentals: Newark, Atlanta, Las Vegas, Fort Lauderdale and San Francisco:

2.租车最昂贵的城市：纽瓦克，亚特兰大，拉斯维加斯，劳德代尔堡和旧金山：

I only included cities which had at least 20 cars operational in the city for a fairer comparison. The cities are ranked from highest median car rental value to lowest. Median is a better metric here than a simple average.

为了更公平地比较，我只包括在该城市运营至少20辆汽车的城市。 这些城市的排名从最高的中位租车价格到最低的排名。 在这里，中位数是比简单平均值更好的指标。

3. Cheapest cities for car rentals: Richmond, Minneapolis, Oklahoma City, San Antonio and Indianapolis.

3.租车最便宜的城市：里士满，明尼阿波利斯，俄克拉荷马城，圣安东尼奥和印第安纳波利斯。

The same figure as above shows these results.

上面相同的图显示了这些结果。

4. Most popular Car models are: Model 3, Mustang, Model S, Wrangler and Model X

4.最受欢迎的汽车模型是：模型3，野马，模型S，牧马人和模型X

Only top 50 models are shown below as number of models were too many.

由于型号太多，因此下面仅显示前50个型号。

One caveat: Because the data was scraped from a particular peer-to-peer car rental website, the dataset is likely skewed towards ‘tech’ workers or millennials who are more likely to use such platforms. But as most of the people in USA are now comfortable using such technology platforms, I think the skew should be tolerable. Moreover, as you — the Medium readers — are likely to fall in that demographic, the skew actually should not really matter.

一个警告：由于数据是从特定的点对点租车网站上抓取的，因此该数据集可能会偏向更可能使用此类平台的“技术”工人或千禧一代。 但是，由于美国大多数人现在对使用这样的技术平台感到满意，所以我认为这种偏斜应该是可以容忍的。 而且，由于您(中级读者)可能会属于该人群，因此偏斜实际上并不应该很重要。

数据集和工具： (The Dataset and Tools:)

I built this data-set by web-scraping using Python. An actual discussion of the same is being left our here for the sake of brevity and time. If you are interested, then do let me know in the comments below.

我通过使用Python进行网页抓取来构建此数据集。 为了简洁和节省时间，我们将在此处进行实际讨论。 如果您有兴趣，请在下面的评论中告诉我。

After scraping the data, I used Jupyter Notebook to do some data wrangling and cleaning. The plots and visualizations themselves have been made using Seaborn and Matplotlib libraries. If you are interested in looking at the code and can wade through some messy details, then have a look at my Github repo.

抓取数据后，我使用Jupyter Notebook进行了一些数据整理和清理。 绘图和可视化本身是使用Seaborn和Matplotlib库制作的。 如果您对查看代码感兴趣并且可以浏览一些凌乱的细节，请查看我的Github回购 。

康奈尔租车数据集 (Cornell Car Rental Dataset)

With this post I am also introducing, what I am going to call as, the Cornell Car Rental Dataset: A Dataset of 5,851 Cars with fields such as Vehicle Make, Model, Year, Daily Fare, Location Details and more. Many of the unnecessary fields and fields with private information have already been removed from this dataset. This will be my small contribution, among others that i have made, to the open source community that I have benefitted tremendously over the course of time.

在这篇文章中，我还将介绍康奈尔汽车租赁数据集：一个5,851辆汽车的数据集，其中包含诸如车辆制造，型号，年份，每日车费，位置详细信息等字段。 许多不必要的字段和带有私人信息的字段已从此数据集中删除。 这将是我对开源社区的一小笔贡献，而这是我长期以来受益匪浅的。

You can download the dataset from my Kaggle repo. Download it and have fun exploring.

您可以从我的Kaggle存储库下载数据集。 下载并享受探索的乐趣。