特斯拉最安全的车_特斯拉现在是最受欢迎的租车选择
特斯拉最安全的車
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.
您是否想知道哪種汽車在美國最受歡迎,在各個城市的典型租金是多少? 作為新興技術(shù)創(chuàng)業(yè)公司Ving Rides的產(chǎn)品和數(shù)據(jù)科學(xué)負(fù)責(zé)人,這些是我要回答的一些問題。 通過此練習(xí),我收集了很多見解,但是為了節(jié)省時間,我將介紹一些最有趣的見解供您使用。
Read on to know these answers presented using some beautiful visualizations.
繼續(xù)閱讀,以了解使用一些精美的可視化呈現(xiàn)的答案。
Photo by Vlad Tchompalov on Unsplash Vlad Tchompalov在Unsplash上的照片見解: (The Insights:)
I’ll list some caveats and other details later, but first let’s dive straight into the findings from this exploration:
稍后我將列出一些注意事項和其他細(xì)節(jié),但首先讓我們直接了解一下本次探索的結(jié)果:
1. Tesla is the most rented car:
1.特斯拉是租金最高的汽車:
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!
緊隨特斯拉之后的是豐田,寶馬,福特和雪佛蘭。 下圖顯示了按日租金計算的汽車制造商,并按其數(shù)量/數(shù)量(即受歡迎程度)從上到下排列。 下面的每個點代表數(shù)據(jù)集中的一輛汽車!
2. Rarest Cars are: McLaren, Saab, Suzuki, Mercury and Genesis
2. 稀有汽車有:邁凱輪,薩博,鈴木,水星和創(chuàng)世紀(jì)
These results can be seen in the previous figure.
這些結(jié)果可以在上圖中看到。
Photo by Jeff Tumale on Unsplash Jeff Tumale在Unsplash上拍攝的照片3. Majority of Car rental fare is between 35–60 Dollar per day range
3.大多數(shù)租車費(fèi)每天在35–60美元之間
2. Most expensive cities for car rentals: Newark, Atlanta, Las Vegas, Fort Lauderdale and San Francisco:
2.租車最昂貴的城市:紐瓦克,亞特蘭大,拉斯維加斯,勞德代爾堡和舊金山:
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.
為了更公平地比較,我只包括在該城市運(yùn)營至少20輛汽車的城市。 這些城市的排名從最高的中位租車價格到最低的排名。 在這里,中位數(shù)是比簡單平均值更好的指標(biāo)。
3. Cheapest cities for car rentals: Richmond, Minneapolis, Oklahoma City, San Antonio and Indianapolis.
3.租車最便宜的城市:里士滿,明尼阿波利斯,俄克拉荷馬城,圣安東尼奧和印第安納波利斯。
The same figure as above shows these results.
上面相同的圖顯示了這些結(jié)果。
4. Most popular Car models are: Model 3, Mustang, Model S, Wrangler and Model X
4.最受歡迎的汽車模型是:模型3,野馬,模型S,牧馬人和模型X
Only top 50 models are shown below as number of models were too many.
由于型號太多,因此下面僅顯示前50個型號。
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.
一個警告:由于數(shù)據(jù)是從特定的點對點租車網(wǎng)站上抓取的,因此該數(shù)據(jù)集可能會偏向更可能使用此類平臺的“技術(shù)”工人或千禧一代。 但是,由于美國大多數(shù)人現(xiàn)在對使用這樣的技術(shù)平臺感到滿意,所以我認(rèn)為這種偏斜應(yīng)該是可以容忍的。 而且,由于您(中級讀者)可能會屬于該人群,因此偏斜實際上并不應(yīng)該很重要。
數(shù)據(jù)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.
我通過使用Python進(jìn)行網(wǎng)頁抓取來構(gòu)建此數(shù)據(jù)集。 為了簡潔和節(jié)省時間,我們將在此處進(jìn)行實際討論。 如果您有興趣,請在下面的評論中告訴我。
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.
抓取數(shù)據(jù)后,我使用Jupyter Notebook進(jìn)行了一些數(shù)據(jù)整理和清理。 繪圖和可視化本身是使用Seaborn和Matplotlib庫制作的。 如果您對查看代碼感興趣并且可以瀏覽一些凌亂的細(xì)節(jié),請查看我的Github回購 。
康奈爾租車數(shù)據(jù)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.
在這篇文章中,我還將介紹康奈爾汽車租賃數(shù)據(jù)集:一個5,851輛汽車的數(shù)據(jù)集,其中包含諸如車輛制造,型號,年份,每日車費(fèi),位置詳細(xì)信息等字段。 許多不必要的字段和帶有私人信息的字段已從此數(shù)據(jù)集中刪除。 這將是我對開源社區(qū)的一小筆貢獻(xiàn),而這是我長期以來受益匪淺的。
You can download the dataset from my Kaggle repo. Download it and have fun exploring.
您可以從我的Kaggle存儲庫下載數(shù)據(jù)集。 下載并享受探索的樂趣。
翻譯自: https://medium.com/@kushlesh.iitb/tesla-is-now-the-most-popular-car-rental-choice-9b47ce18c9c8
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