Python 为列中的每个唯一项目执行距离计算的函数或嵌套循环

Question

基本上可以说我有 3 辆车和一堆 x/y 坐标如下：

车号___ x坐标___ y坐标
1 _____________ 54 _____ 25
1 _____________ 57 _____ 26
1 _____________ 54 _____ 29
2 _____________ 52 _____ 24
2 _____________ 56 _____ 28
2 _____________ 57 _____ 29
3 _____________ 51 _____ 25
3 _____________ 54 _____ 26
3 _____________ 59 _____ 29

我需要我的代码做的是根据坐标计算每辆车的位移或行驶距离，输出显示类似

汽车__排量
1 ________ 9
2 ________ 5
3 ________ 7

我现在有的在下面，肯定不行

displacement  = 0
for (car number, x coor, y coor) in coorset:
    for i in car number:
        displacement(i) = displacement  + (df[coor x] **2 + df[coor y] **2)**.5
        print (displacement)
        print(car number)

我是 python 的新手，所以请原谅我的错误，我真的很困惑。

Answer 1

from pandas import DataFrame

# create data
data = DataFrame([
    (1, 54, 25),
    (1, 57, 26),
    (1, 54, 29),
    (2, 52, 24),
    (2, 56, 28),
    (2, 57, 29),
    (3, 51, 25),
    (3, 54, 26),
    (3, 59, 29),
], columns=['car_number', 'x_coord', 'y_coord'])


# calculate distances
data['distance'] = (
    (data['x_coord'] - data['x_coord'].shift()) ** 2 +
    (data['y_coord'] - data['y_coord'].shift()) ** 2
) ** 0.5

# ignore distances between points for different cars
data['same_car'] = data['car_number'] == data['car_number'].shift()
data['distance'] = data['distance'] * data['same_car']

# group distances by car and sum
distances = data.groupby('car_number')['distance'].sum().reset_index()

Answer 2

这应该有效。我截取了当前车号对应的dataframe的一部分，修改它以包含位移，然后在原始dataframe中替换它。

data["displacement"] = 0

def distance_x(df, i):
        return (df.iloc[i, 1] - df.iloc[i + 1, 1]) ** 2

def distance_y(df, i):
    return (df.iloc[i, 2] - df.iloc[i + 1, 2]) ** 2

def total_displacement(df):
    cars = df["car_number"].unique()
    for car_num in cars:
        df_sel = df[df["car_number"] == car_num].copy()
        for i in range(len(df_sel) - 1):
            distance = (distance_x(df_sel, i) + distance_y(df_sel, i)) ** (1/2)
            df_sel.iloc[i + 1, 3] = distance + df_sel.iloc[i, 3]
        df[df["car_number"] == df_sel.iloc[0,0]] = df_sel    
    return df
    
total_displacement(data)
print(data)

 car_number  x_coord  y_coord  displacement
0         1.0     54.0     25.0      0.000000
1         1.0     57.0     26.0      3.162278
2         1.0     54.0     29.0      7.404918
3         2.0     52.0     24.0      0.000000
4         2.0     56.0     28.0      5.656854
5         2.0     57.0     29.0      7.071068
6         3.0     51.0     25.0      0.000000
7         3.0     54.0     26.0      3.162278
8         3.0     59.0     29.0      8.993230

Python 为列中的每个唯一项目执行距离计算的函数或嵌套循环

Python function or nested loop that does a distance calculation for each unique item in column

python

loops

nested

distance

nested-loops