网络服务器租赁费用

by Zhen Liu

刘震

如何分析租赁季节性和趋势以节省租赁费用 (How to Analyze Rental Seasonality and Trend to Save Money on Your Lease)

When I was looking for a new apartment to rent, I started to wonder: is there any seasonality impact? Is there a month when the rent is lowest so I can save money when I start my lease?

当我要租一间新公寓时，我开始怀疑：这会对季节性产生影响吗？ 是否有一个月的最低租金，以便我可以在开始租赁时省钱？

To tackle this question, I used Zillow’s public data here. I analyzed their one-bedroom rental data from January, 2011 to September, 2017 for the top 100 US cities ranked by size.

为了解决这个问题，我在这里使用了Zillow的公开数据。 我分析了其2011年1月至2017年9月按规模排名的美国前100个城市的一居室租金数据。

The short answer is YES. You can save from $1000 to $2000 if you pick the right month to start renting in certain cities. By simply fitting a linear regression model using time and month to estimate rent, I found some interesting seasonality patterns for a few cities.

简短的答案是“是” 。 如果您选择合适的月份开始在某些城市租房，则可以节省1000至2000美元 。 通过简单地使用时间和月份来估算租金来拟合线性回归模型，我发现了一些城市的一些有趣的季节性模式。

Methodology:

方法：

On the high level, rent = trend + seasonality. I fit a linear regression model for each city to breakdown trend and seasonality (using a cycle of 12 months).

在较高的水平上， 租金=趋势+季节性 。 我为每个城市拟合了线性回归模型以分解趋势和季节性(使用12个月的周期)。

Model: estimated rent(for a specific month)=t+t²+m1+m2+m3+…+m12

型号：预计租金(特定月份)= t +t²+ m1 + m2 + m3 +…+ m12

Variables: t and t² are continuous variables to estimate trend; t is the count of months from the beginning month in a city. I added t² to adjust for quadratic trend, and you’ll see some clear curves in the plot of Philadelphia below.

变量： t和 t²是估计趋势的连续变量； t是从城市开始的月份开始的月份数。 我加了t² 调整二次趋势，您将在下面的费城图中看到一些清晰的曲线。

m1, m2, … , m12 are binary variables (0 or 1) that indicate to which month one data point (rent) belongs. Each rent data point can only be assigned one of the monthly variable (as 1). The rest will be 0.

m1 ， m2 ，…， m12是二进制变量(0或1)，指示一个数据点(租金)属于哪个月。 每个租金数据点只能分配一个月度变量(为1)。 其余为0。

After fitting the model above for all cities, I counted how many months’ coefficients were statistically significantly higher than the month estimated to have the lowest rent. I considered cities with a count ≥3 to have a potentially large seasonality effect.

在对所有城市都采用上述模型后，我计算了统计得出的多少个月的租金比估计最低租金的月份高得多。 我认为计数≥3的城市可能具有较大的季节性影响。

Then I examined the the overall model fitting to filter out cities with a lot of noise, and came up with a final list of the six most representative cities.

然后，我检查了整体模型拟合，以筛选出噪音很大的城市，并得出了六个最具代表性的城市的最终清单。

Now I’m going to show you these cities so you can see the sweetest month for you to start renting. I plotted the simulated rent against the actual rent below. You can see the pure seasonal difference (adjusted by each city’s trend) for each month on the lower right corner. Here’s how to read the plots:

现在，我将向您展示这些城市，以便您可以看到最甜蜜的月份开始租房。 我将模拟租金与实际租金进行了对比。 您可以在右下角看到每个月的纯季节性差异(根据每个城市的趋势进行调整)。 这是读取图的方法：

Black line: actual rent data

黑线 ：实际租金数据

Green line: simulated rent by regression model given month and year

绿线 ：按月和年给出的回归模型模拟租金

Green bar plot on the right corner: pure seasonal effect estimated by model

右上角的绿色条形图 ：模型估算的纯季节性影响

Grey line: estimated trend by regression model

灰线 ：通过回归模型估算的趋势

Seasonal gap: highest rent minus lowest rent (the difference estimated between the highest and lowest point from the regression model without trend effect)

季节性差距 ：最高租金减去最低租金(通过回归模型估算的最高点和最低点之间的差异，没有趋势效应)

Numerical labels: represent the months estimated to have highest (red) and lowest (blue) rent

数字标签 ：代表估计租金最高(红色)和最低(蓝色)的月份

季节性影响显着的六个城市 (Six Cities with Significant Seasonality Effect)

You’ll definitely save money if you start renting on a “low” month in these cities.

如果您在这些城市中的“低”月开始租房，肯定会省钱。

1. Boston

   波斯顿

If you start renting in June, you’ll save about $2484 a year (207*12) compared to starting a lease in November. The grey line shows a slight trend in Boston, but it’s not very significant compared to the strong seasonal factor.

如果您从6月开始租房，与11月开始租房相比，您每年将节省约2484美元 (207 * 12)。 灰线显示的是波士顿的轻微趋势，但与强劲的季节性因素相比并不十分显着。

2. Minneapolis

2. 明尼阿波利斯

There is a slight upward trend, but the seasonality effect is more significant than the trend. Your yearly savings, if renting from December, can be as high as $1896 (158*12). In reality, this number is likely to be slightly lower, because the upward trend tends to shrink the difference a bit.

趋势略有上升，但季节性效应比趋势更为明显。 如果您从12月开始租房，则每年的储蓄额可高达$ 1896 (158 * 12)。 实际上，这个数字可能会略低一些，因为上升趋势倾向于使差异有所缩小。

3. Philadelphia

3.费城

After the regression model’s adjustment for the curve-shaped trend, the estimated yearly saving on rent is $1404 (117*12). This number is greater during the period with a downward trend: you can see that the distance between January and May’s rent is stretched further prior to 2014. The estimated savings are smaller when the overall rent increased during recent years.

在对曲线趋势进行回归模型调整后，估计每年节省的租金为$ 1404 (117 * 12)。 在此期间，这个数字更大，并且呈下降趋势：您可以看到1月份和5月份的租金之间的距离在2014年之前进一步拉长。当近年来的总体租金增加时，预计节省的费用会减少。

4. Chicago

4.芝加哥

The overall trend in Chicago is actually the opposite of Philadelphia’s — it went up and then down. But the seasonality effect is still significant after adjusting for trend. The estimated yearly saving is $1248 (104*12). If the downward trend continues, the saving will be greater — the rent distance between November and April is stretched further as plotted in recent years.

芝加哥的总体趋势实际上与费城相反-上升然后下降。 但是，在调整趋势之后，季节性影响仍然显着。 估计每年可节省$ 1248 (104 * 12)。 如果这种下降趋势继续下去，节省的费用将更多—近年来，11月和4月之间的租金距离进一步拉长。

5. Columbus

5.哥伦布

There is a noticeable upward trend in Columbus’s rent, but the seasonality effect is also quite significant. The estimated yearly savings are smaller after adjusting the pure seasonal gap ($89) by the upward trend, so you’d save around $720 (60*12). But you should still consider starting your lease in November and avoiding August.

哥伦布的租金有明显的上升趋势，但季节性影响也非常明显。 在按上升趋势调整纯季节性差异($ 89)后，估计每年节省的费用较小，因此您将节省约720美元 (60 * 12)。 但是您仍然应该考虑在11月开始租用，避免使用8月。

6. Woodbridge

6.伍德布里奇

If you start renting in December, you’ll save about $948 (79*12) a year compared to renting from July. The trend isn’t very significant here, so it’s still seasonality that drives the rent price in Woodbridge.

如果您从12月开始租房，那么与7月相比，每年将节省948美元 (79 * 12)。 这里的趋势不是很明显，因此仍然是季节性因素决定了伍德布里奇的租金价格。

What about Seattle, the city where I live?

那我居住的城市西雅图呢？

The seasonality effect also exists in Seattle, and it shows significance in the regression model. However, the trend is so big that the seasonality almost doesn’t matter.

西雅图也存在季节性效应，它在回归模型中显示出重要意义。 但是，这种趋势是如此之大，以至于季节性几乎无关紧要。

Even so, understanding the seasonality for cities like Seattle can be helpful. While you might not able to negotiate the rent down that much in a less busy season, you could ask that the application fee be waived or something like that.

即使这样，了解西雅图等城市的季节性也会有所帮助。 虽然您可能无法在较不繁忙的季节中就这么低的租金进行协商，但是您可以要求免除申请费或类似费用。

My current apartment waived mine when I started my lease in January — December has the lowest rent, followed by January. But they might not offer this perk in the busiest months with higher rents, like May and June.

当我在一月份开始租房时，我目前的公寓放弃了我的住所-12月的租金最低，其次是1月。 但是在五月和六月等最繁忙的月份，他们可能无法提供这种津贴。

Another city where the trend outweighs the seasonality is Omaha.

奥马哈是另一个趋势超过季节性的城市。

Knowing your city’s seasonality in rent can help you save thousands if you know the pattern. I did my analysis and plots using R, but you can simply plot your city’s data in Excel if you just want to see if there are any noticeable trend and seasonality. Using open source data to hack your life decisions and save money is actually pretty simple.

如果您知道城市的租金季节性，则可以了解成千上万种方式。 我使用R进行了分析和绘图，但是如果您只想查看是否存在任何明显的趋势和季节性，则可以在Excel中简单地绘制城市数据。 实际上，使用开源数据来破解您的生活决策并节省资金是非常简单的。

现在，您应该签署多长时间的租约？ (Now, how long should you sign your lease?)

Say you are offered a few different options for the length of your lease. Usually it’s nine months to 18 months. Do you know what’s the best length to choose when you sign your lease? There is actually another trick to save money when you pick the duration, and I’ll show you the trick and the math behind it in my next post.

假设您在租约期限内有几种选择。 通常是9个月到18个月。 您知道签署租约时最合适的长度吗？ 当您选择持续时间时，实际上还有另一个省钱的窍门，我将在下一篇文章中向您展示该窍门及其背后的数学原理。

Give me a few claps and share this with friends who might find it useful!

给我一些鼓掌，并与可能会觉得有用的朋友分享！

You can find my code here.

您可以在这里找到我的代码 。

翻译自: https://www.freecodecamp.org/news/how-to-analyze-seasonality-and-trends-to-save-money-on-your-apartment-lease-714d1d82771a/

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