擅长:python、mysql、java
<p>即使你自己似乎没有做过任何研究,你也可以这样做:
短谷歌搜索结果:<a href="https://geopy.readthedocs.io/en/stable/#module-geopy.distance" rel="nofollow noreferrer">https://geopy.readthedocs.io/en/stable/#module-geopy.distance</a></p>
<p>通过实践,您现在可以相对轻松地了解如何访问熊猫中的DF并应用操作(@wwnde已经展示了这一点)</p>
<p>将这两个基本要素结合起来可以:</p>
<pre><code>import pandas as pd
import numpy as np
from geopy import distance
# Generate some random data (lon, lat must be in (-90, 90)
df = pd.DataFrame(np.random.randint(-90, 90, size=(100, 4)), columns=list(['lo1', 'la1', 'lo2', 'la2']))
print(df)
# applies the distance function as described in the provided link
df['km'] = df.apply(lambda x: distance.distance((x[0], x[1]), (x[2], x[3])), axis=1)
print(df)
</code></pre>
<p>此外,我发现<a href="https://stackoverflow.com/questions/55909305/using-geopy-in-a-dataframe-to-get-distances">this</a>是第一个链接,但没有阅读它,因为解决方案非常简单</p>
<p>正如StackOverflow的CoC所建议的那样,请提供您已经尝试过的,并且具有正确的行为,以便简单地查看google</p>