合并度分数据列，处理进位到下一个度数。（Python）

Question

我遇到了一种奇怪的数据格式，正在为此烦恼。这是一个CSV文件，里面有一个时间戳列，还有一个表示纬度分钟的列（是个小数），以及一个表示经度分钟的列（也是小数）。数据中还包含一个起始的纬度和经度（以度为单位），但只有一个起始值。我需要把纬度和经度的分钟列与起始值结合起来，并转换成度和小数度的格式。我对这种格式感到困惑。

lat = 45
long = 75

data = {
    'time': [
        '2024-03-27 12:00:00', '2024-03-27 12:00:01', '2024- 03-27 12:00:02', '2024-03-27 12:00:03', '2024-03-27 12:00:04', '2024-03-27 12:00:05'
    ],
    'lat_minutes': [
        59.9955, 59.9963, 0.0180, 0.0230, 0.0050, 59.6500
    ],
    'long_minutes': [
        59.0250, 59.0750, 0.0020, 0.1850, 0.0750, 59.075
    ]
}

df = pd.DataFrame(data)


    time                 lat_minutes       long_minutes
0   2024-03-27 12:00:00  59.9955            59.025
1   2024-03-27 12:00:01  59.9963            59.075
2   2024-03-27 12:00:02  0.0180             0.002
3   2024-03-27 12:00:03  0.0230             0.185
4   2024-03-27 12:00:04  0.0050             0.075
5   2024-03-27 12:00:05  59.6500            59.075

我需要输出一个新列，格式是度.小数，计算方法是把分钟列的值加到起始的纬度和经度值上。当分钟超过60时，要加上一个完整的度；如果分钟在减少并且超过了0，变成59.9999时，则要减去一个度。

输出应该是这样的：

    time                 lat_minutes  long_minutes   Latitude  Longitude
0   2024-03-27 12:00:00  59.9955         59.025     45.999925   75.98375      
1   2024-03-27 12:00:01  59.9963         59.075     45.9999383  75.984583
2   2024-03-27 12:00:02  0.0180          0.002      46.00030    76.0003
3   2024-03-27 12:00:03  0.0230          0.185      46.00383    76.00308 
4   2024-03-27 12:00:04  0.0050          0.075      46.00125    76.00125
5   2024-03-27 12:00:05  59.6500         59.075     45.99416    75.98458

Answer 1

我猜你是在寻找类似下面的内容：

def formDegrees(degree:float, offset: float) -> float:
    # create a decinmal degree value from datum  + offset
    if int(degree) == degree and offset < 60.0:
        # The simple case 
        return degree + offset/60
    deg_frac = (degree -int(degree))*60
    deg_frac += offset
    return int(degree) + deg_frac/60

使用这个函数，给出以下内容：

start_lat = 45
lat_minutes = [59.9955, 59.9963, 60.0180, 60.0230, 60.0050, 59.6500]

执行：

for offset in lat_minutes]:
    print (offset, formDegrees(start_lat, offset))

得到的结果是：

59.9955 45.999925
59.9963 45.99993833333333
60.018 46.0003
60.023 46.00038333333333
60.005 46.000083333333336
59.65 45.994166666666665

Answer 2

我相信这段代码可以简化得更短，但现在这样也能正常工作（经度的代码可以重复使用）。

# calculate how much the minutes changed since the preceding row
delta = df['lat_minutes'] - df['lat_minutes'].shift(1)

# initialise the new degrees column to all zeros
df['lat'] = 0

# if minutes decreases by more than 30
# treat it as having moved forward over a degree boundary
# => record a +1 degree offset at that row
df.loc[delta < -30, 'lat'] += 1

# if minutes increases by more than 30
# treat it as having moved backward over a degree boundary
# => record a -1 degree offset at that row
df.loc[delta >  30, 'lat'] -= 1

# final degrees = cumulative sum of above 'offsets', plus base offset, plus minutes/60
df['lat'] = df['lat'].cumsum() + lat + df['lat_minutes'] / 60

演示链接： https://www.online-python.com/rKvMuwq2sC

补充：也许可以稍微整理得更好一些……

delta = df['lat_minutes'] - df['lat_minutes'].shift(1)

offset = (
  (delta < -30).astype(int)
  -
  (delta >  30).astype(int)
)

df['lat'] = offset.cumsum() + lat + df['lat_minutes'] / 60

最终演示链接： https://www.online-python.com/7hdsye2VHE