如何根据最新日期时间更新坐标？

Question

你想知道如何根据记录的日期来更新坐标。比如说，6月27日没有观察到数据，但如果我假设两辆车在朝同一个方向以和最后一次观察时相同的速度行驶，那我该如何更新坐标，以便使用最近一次记录的经纬度来计算距离呢？

import pandas as pd

# Car 1
car1_data = {
    'id': ['id0120169', 'id0386349', 'id1962532', 'id0335207', 'id0273508'],
    'date_recorded': ['7/1/2016 9:05', '6/29/2016 22:26', '6/29/2016 2:47', '6/26/2016 22:29', '6/25/2016 19:19'],
    'longitude': [-73.99017334, -73.97213745, -73.91963959, -73.98487091, -73.99116516],
    'latitude': [40.75667953, 40.75746155, 40.80377579, 40.76160812, 40.75000763],
    'rate': [50, 67, 43, 35, 46],
    'direction': ['N', 'E', 'E', 'S', 'W']}
car1_df = pd.DataFrame(car1_data)

# Car 2
car2_data = {
    'id': ['id2681896', 'id3308448', 'id2108525', 'id3952220', 'id2771348'],
    'date_recorded': ['6/30/2016 23:59', '6/29/2016 19:33', '6/28/2016 20:50', '6/26/2016 21:07', '6/25/2016 18:46'],
    'longitude': [-73.9881286621093, -73.9656295776367, -73.9716567993164, -73.9820938110351, -73.9761657714843],
    'latitude': [40.7320289611816, 40.7527198791503, 40.7945442199707, 40.7694053649902, 40.7602424621582],
    'rate': [81, 76, 59, 48, 55],
    'direction': ['S', 'E', 'N', 'W', 'W']}
car2_df = pd.DataFrame(car2_data)

Answer 1

你需要做的是根据每辆车最后观察到的方向和速度来计算它们的移动。如果我们假设这两辆车在6月27日之前的最后观察后，会沿着最后观察到的方向移动24小时。

根据你的数据：

import pandas as pd

car1_data = {
    'id': ['id0120169', 'id0386349', 'id1962532', 'id0335207', 'id0273508'],
    'date_recorded': ['7/1/2016 9:05', '6/29/2016 22:26', '6/29/2016 2:47', '6/26/2016 22:29', '6/25/2016 19:19'],
    'longitude': [-73.99017334, -73.97213745, -73.91963959, -73.98487091, -73.99116516],
    'latitude': [40.75667953, 40.75746155, 40.80377579, 40.76160812, 40.75000763],
    'rate': [50, 67, 43, 35, 46],
    'direction': ['N', 'E', 'E', 'S', 'W']}
car1_df = pd.DataFrame(car1_data)

car2_data = {
    'id': ['id2681896', 'id3308448', 'id2108525', 'id3952220', 'id2771348'],
    'date_recorded': ['6/30/2016 23:59', '6/29/2016 19:33', '6/28/2016 20:50', '6/26/2016 21:07', '6/25/2016 18:46'],
    'longitude': [-73.9881286621093, -73.9656295776367, -73.9716567993164, -73.9820938110351, -73.9761657714843],
    'latitude': [40.7320289611816, 40.7527198791503, 40.7945442199707, 40.7694053649902, 40.7602424621582],
    'rate': [81, 76, 59, 48, 55],
    'direction': ['S', 'E', 'N', 'W', 'W']}
car2_df = pd.DataFrame(car2_data)

你应该定义以下函数，用来更新位置并预测相对于之前位置的新位置：

def update_position(row, hours=24):
    delta = row['rate'] * 0.001 * hours
    if row['direction'] == 'N':
        return row['latitude'] + delta, row['longitude']
    elif row['direction'] == 'S':
        return row['latitude'] - delta, row['longitude']
    elif row['direction'] == 'E':
        return row['latitude'], row['longitude'] + delta
    elif row['direction'] == 'W':
        return row['latitude'], row['longitude'] - delta

def preprocess_df(df):
    df['date_recorded'] = pd.to_datetime(df['date_recorded'])
    df.sort_values('date_recorded', inplace=True)

def predict_positions(df, missing_date):
    """
    Predict positions for a given date assuming constant movement from the last recorded position.
    """
    preprocess_df(df)
    df_before_missing = df[df['date_recorded'] < pd.to_datetime(missing_date)].copy()
    if df_before_missing.empty:
        return df
    last_observation = df_before_missing.iloc[-1]
    new_lat, new_long = update_position(last_observation)
    new_row = pd.DataFrame([{
        'id': last_observation['id'],
        'date_recorded': pd.to_datetime(missing_date),
        'longitude': new_long,
        'latitude': new_lat,
        'rate': last_observation['rate'],
        'direction': last_observation['direction']
    }])
    df_updated = pd.concat([df, new_row], ignore_index=True)
    return df_updated

那么，对于你想要的日期：

missing_date = '6/27/2016'
car1_df_updated = predict_positions(car1_df, missing_date)
car2_df_updated = predict_positions(car2_df, missing_date)

你会得到车1的结果

          id       date_recorded  longitude   latitude  rate direction
0  id0273508 2016-06-25 19:19:00 -73.991165  40.750008    46         W
1  id0335207 2016-06-26 22:29:00 -73.984871  40.761608    35         S
2  id1962532 2016-06-29 02:47:00 -73.919640  40.803776    43         E
3  id0386349 2016-06-29 22:26:00 -73.972137  40.757462    67         E
4  id0120169 2016-07-01 09:05:00 -73.990173  40.756680    50         N
5  id0335207 2016-06-27 00:00:00 -73.984871  39.921608    35         S

还有车2的结果

          id       date_recorded  longitude   latitude  rate direction
0  id2771348 2016-06-25 18:46:00 -73.976166  40.760242    55         W
1  id3952220 2016-06-26 21:07:00 -73.982094  40.769405    48         W
2  id2108525 2016-06-28 20:50:00 -73.971657  40.794544    59         N
3  id3308448 2016-06-29 19:33:00 -73.965630  40.752720    76         E
4  id2681896 2016-06-30 23:59:00 -73.988129  40.732029    81         S
5  id3952220 2016-06-27 00:00:00 -75.134094  40.769405    48         W