我在Python 2.7的Pandas DataFrame中有以下内容:
Ser_Numb LAT LONG
1 74.166061 30.512811
2 72.249672 33.427724
3 67.499828 37.937264
4 84.253715 69.328767
5 72.104828 33.823462
6 63.989462 51.918173
7 80.209112 33.530778
8 68.954132 35.981256
9 83.378214 40.619652
10 68.778571 6.607066
我想计算数据框中相邻行之间的距离。输出结果应该类似于这个样子:
Ser_Numb LAT LONG Distance
1 74.166061 30.512811 0
2 72.249672 33.427724 d_between_Ser_Numb2 and Ser_Numb1
3 67.499828 37.937264 d_between_Ser_Numb3 and Ser_Numb2
4 84.253715 69.328767 d_between_Ser_Numb4 and Ser_Numb3
5 72.104828 33.823462 d_between_Ser_Numb5 and Ser_Numb4
6 63.989462 51.918173 d_between_Ser_Numb6 and Ser_Numb5
7 80.209112 33.530778 .
8 68.954132 35.981256 .
9 83.378214 40.619652 .
10 68.778571 6.607066 .
尝试
这篇文章看起来有些类似,但它计算的是固定点之间的距离。我需要相邻点之间的距离。
我尝试将其调整为以下内容:
df['LAT_rad'], df['LON_rad'] = np.radians(df['LAT']), np.radians(df['LONG'])
df['dLON'] = df['LON_rad'] - np.radians(df['LON_rad'].shift(1))
df['dLAT'] = df['LAT_rad'] - np.radians(df['LAT_rad'].shift(1))
df['distance'] = 6367 * 2 * np.arcsin(np.sqrt(np.sin(df['dLAT']/2)**2 + math.cos(df['LAT_rad'].astype(float).shift(-1)) * np.cos(df['LAT_rad']) * np.sin(df['dLON']/2)**2))
然而,我收到了以下错误:
Traceback (most recent call last):
File "C:\Python27\test.py", line 115, in <module>
df['distance'] = 6367 * 2 * np.arcsin(np.sqrt(np.sin(df['dLAT']/2)**2 + math.cos(df['LAT_rad'].astype(float).shift(-1)) * np.cos(df['LAT_rad']) * np.sin(df['dLON']/2)**2))
File "C:\Python27\lib\site-packages\pandas\core\series.py", line 78, in wrapper
"{0}".format(str(converter)))
TypeError: cannot convert the series to <type 'float'>
[Finished in 2.3s with exit code 1]
这个错误已经通过MaxU的评论得到修复。修复后,这个计算的输出结果不合理——距离近乎8000千米:
Ser_Numb LAT LONG LAT_rad LON_rad dLON dLAT distance
0 1 74.166061 30.512811 1.294442 0.532549 NaN NaN NaN
1 2 72.249672 33.427724 1.260995 0.583424 0.574129 1.238402 8010.487211
2 3 67.499828 37.937264 1.178094 0.662130 0.651947 1.156086 7415.364469
3 4 84.253715 69.328767 1.470505 1.210015 1.198459 1.449943 9357.184623
4 5 72.104828 33.823462 1.258467 0.590331 0.569212 1.232802 7992.087820
5 6 63.989462 51.918173 1.116827 0.906143 0.895840 1.094862 7169.812123
6 7 80.209112 33.530778 1.399913 0.585222 0.569407 1.380421 8851.558260
7 8 68.954132 35.981256 1.203477 0.627991 0.617777 1.179044 7559.609520
8 9 83.378214 40.619652 1.455224 0.708947 0.697986 1.434220 9194.371978
9 10 68.778571 6.607066 1.200413 0.115315 0.102942 1.175014 NaN
根据:
- 使用这个在线计算器: 如果我使用 纬度1 = 74.166061, 经度1 = 30.512811, 纬度2 = 72.249672, 经度2 = 33.427724, 那么得到的距离是233公里
- 在这里找到的haversine函数为:
print haversine(30.512811, 74.166061, 33.427724, 72.249672)
,然后我得 到232.55公里
答案应该是233公里,但我的方法却给出了约8000公里。我认为我在尝试迭代相邻行时出现了问题。
问题:有没有一种方法可以在Pandas中完成此操作?还是需要逐行循环数据帧?
额外信息:
要创建上面的DF,请选择它并复制到剪贴板。然后:
import pandas as pd
df = pd.read_clipboard()
print df
math.cos
替换为np.cos
- MaxU - stand with Ukraine