Добавление данных из фрейма данных в файл json без удаления предыдущего содержимого - PullRequest
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Добавление данных из фрейма данных в файл json без удаления предыдущего содержимого

0 голосов
/ 03 июня 2018

Позвольте мне начать с того, что я очень новичок, и этот код, вероятно, ужасен.Я пытаюсь добавить данные фрейма данных в файл json, не удаляя предыдущее содержимое данных json при каждом последующем запуске. 

import json
import pandas as pd
import datetime

json_backup = 'temp.json'
df_store = pd.DataFrame(columns=["Time", "Average Rate"])

while True:
   #doing some data gathering (code not included here) at each loop
   df_store = df_store.append({
             "Time": datetime.datetime.now(),
            "Average Rate": average_rate
             }, ignore_index=True)
  df_store.to_json(json_backup)

backup = pd.read_json(json_backup)
print (backup)

Таким образом, это работает, как и предполагалось, со всеми новыми данными, добавляемыми в json, пока яперезапустите скрипт, и данные JSON будут удалены.Как мне поступить так, чтобы эти данные сохранялись и все новые данные просто добавлялись в файл json?

Ответы [ 2 ]

0 голосов
/ 03 июня 2018

@ Тамис , попробуйте следующий код Just copy the code(Python3), paste, run:

Примечание: Я принял начальное значение average_rate как часть микросекунды datetime.now () только для проверки кода.Вы можете рассчитать его значение на основе вашей логики, поэтому, пожалуйста, измените его.

Вам не нужно создавать файл temp.json .Он будет создан автоматически.

Просто скопируйте содержимое файла append_data_to_json-v2-py3.py , вставьте и запустите.

Нажмите Y / y для продолжения после каждого обновления temp.json , в противном случае нажмите любую другую клавишу для выхода из цикла while.

"append_data_to_json-v2-py3.py 

import json
import pandas as pd
import datetime
import time # {Added}

json_backup = 'temp.json'
df_store = pd.DataFrame(columns=["Time", "Average Rate"])

average_rate = 50  # {Added}
count = 1          # {Added}

while True:
    # Doing some data gathering (code not included here) at each loop
    time_data = str(datetime.datetime.now())

    # Store micro seconds of datetime as average 
    # (For test only, use your own logic to calculate it)
    # In case of 2018-06-03 18:44:56.220778 => 220778
    average_rate = int((time_data.split()[1]).split('.')[1]) 

    try:
        df_store = pd.read_json(json_backup)

        df_store = df_store.append({
            "Time": time_data,
            "Average Rate": average_rate
        }, ignore_index=True)

        df_store.to_json(json_backup)
        print (df_store)
        print ("***********************************************")       
    except Exception as e:
        df_store = df_store.append({
            "Time": time_data,
            "Average Rate": average_rate
            }, ignore_index=True)

        df_store.to_json(json_backup)
        print(df_store)
        print("***********************************************")

    # time.sleep(30.0 - ((time.time() - starttime) % 30.0))  # {Commented}
    print(count, "temp.json updated")

    # If user presses Y/y then continue otherwise exit from loop
    choice = input("\n" + str(count) + " Do you want to continue the operation (Y/N): ")
    if choice == 'y' or choice == 'Y':
        count = count + 1
        continue
    else:
        break

"Первый запуск 

(py3.6) H:\RishikeshAgrawani\Projects\Python3\Pandas>python append_data_to_json-v2-py3.py
                         Time Average Rate
0  2018-06-03 18:51:57.506959       506959
***********************************************
1 temp.json updated

1 Do you want to continue the operation (Y/N): y
                         Time  Average Rate
0  2018-06-03 18:51:57.506959        506959
1  2018-06-03 18:52:00.925554        925554
***********************************************
2 temp.json updated

2 Do you want to continue the operation (Y/N): y
                         Time  Average Rate
0  2018-06-03 18:51:57.506959        506959
1  2018-06-03 18:52:00.925554        925554
2  2018-06-03 18:52:02.325613        325613
***********************************************
3 temp.json updated

3 Do you want to continue the operation (Y/N): y
                         Time  Average Rate
0  2018-06-03 18:51:57.506959        506959
1  2018-06-03 18:52:00.925554        925554
2  2018-06-03 18:52:02.325613        325613
3  2018-06-03 18:52:03.508673        508673
***********************************************
4 temp.json updated

4 Do you want to continue the operation (Y/N): y
                         Time  Average Rate
0  2018-06-03 18:51:57.506959        506959
1  2018-06-03 18:52:00.925554        925554
2  2018-06-03 18:52:02.325613        325613
3  2018-06-03 18:52:03.508673        508673
4  2018-06-03 18:52:07.772553        772553
***********************************************
5 temp.json updated

5 Do you want to continue the operation (Y/N): n

" Второй запуск: 

(py3.6) H:\RishikeshAgrawani\Projects\Python3\Pandas>python append_data_to_json-v2-py3.py
                       Time  Average Rate
0  2018-06-03 18:51:57.506959        506959
1  2018-06-03 18:52:00.925554        925554
2  2018-06-03 18:52:02.325613        325613
3  2018-06-03 18:52:03.508673        508673
4  2018-06-03 18:52:07.772553        772553
5  2018-06-03 18:53:52.484954        484954
***********************************************
1 temp.json updated

1 Do you want to continue the operation (Y/N): y
                       Time  Average Rate
0  2018-06-03 18:51:57.506959        506959
1  2018-06-03 18:52:00.925554        925554
2  2018-06-03 18:52:02.325613        325613
3  2018-06-03 18:52:03.508673        508673
4  2018-06-03 18:52:07.772553        772553
5  2018-06-03 18:53:52.484954        484954
6  2018-06-03 18:53:54.733274        733274
***********************************************
2 temp.json updated

2 Do you want to continue the operation (Y/N): y
                       Time  Average Rate
0  2018-06-03 18:51:57.506959        506959
1  2018-06-03 18:52:00.925554        925554
2  2018-06-03 18:52:02.325613        325613
3  2018-06-03 18:52:03.508673        508673
4  2018-06-03 18:52:07.772553        772553
5  2018-06-03 18:53:52.484954        484954
6  2018-06-03 18:53:54.733274        733274
7  2018-06-03 18:53:57.037358         37358
***********************************************
3 temp.json updated

3 Do you want to continue the operation (Y/N): y
                       Time  Average Rate
0  2018-06-03 18:51:57.506959        506959
1  2018-06-03 18:52:00.925554        925554
2  2018-06-03 18:52:02.325613        325613
3  2018-06-03 18:52:03.508673        508673
4  2018-06-03 18:52:07.772553        772553
5  2018-06-03 18:53:52.484954        484954
6  2018-06-03 18:53:54.733274        733274
7  2018-06-03 18:53:57.037358         37358
8  2018-06-03 18:53:58.437644        437644
***********************************************
4 temp.json updated

4 Do you want to continue the operation (Y/N): y
                       Time  Average Rate
0  2018-06-03 18:51:57.506959        506959
1  2018-06-03 18:52:00.925554        925554
2  2018-06-03 18:52:02.325613        325613
3  2018-06-03 18:52:03.508673        508673
4  2018-06-03 18:52:07.772553        772553
5  2018-06-03 18:53:52.484954        484954
6  2018-06-03 18:53:54.733274        733274
7  2018-06-03 18:53:57.037358         37358
8  2018-06-03 18:53:58.437644        437644
9  2018-06-03 18:53:59.181472        181472
***********************************************
5 temp.json updated

5 Do you want to continue the operation (Y/N): y
                        Time  Average Rate
0   2018-06-03 18:51:57.506959        506959
1   2018-06-03 18:52:00.925554        925554
2   2018-06-03 18:52:02.325613        325613
3   2018-06-03 18:52:03.508673        508673
4   2018-06-03 18:52:07.772553        772553
5   2018-06-03 18:53:52.484954        484954
6   2018-06-03 18:53:54.733274        733274
7   2018-06-03 18:53:57.037358         37358
8   2018-06-03 18:53:58.437644        437644
9   2018-06-03 18:53:59.181472        181472
10  2018-06-03 18:53:59.805276        805276
***********************************************
6 temp.json updated

6 Do you want to continue the operation (Y/N): y
                        Time  Average Rate
0   2018-06-03 18:51:57.506959        506959
1   2018-06-03 18:52:00.925554        925554
2   2018-06-03 18:53:59.805276        805276
3   2018-06-03 18:52:02.325613        325613
4   2018-06-03 18:52:03.508673        508673
5   2018-06-03 18:52:07.772553        772553
6   2018-06-03 18:53:52.484954        484954
7   2018-06-03 18:53:54.733274        733274
8   2018-06-03 18:53:57.037358         37358
9   2018-06-03 18:53:58.437644        437644
10  2018-06-03 18:53:59.181472        181472
11  2018-06-03 18:54:00.436774        436774
***********************************************
7 temp.json updated

7 Do you want to continue the operation (Y/N): y
                        Time  Average Rate
0   2018-06-03 18:51:57.506959        506959
1   2018-06-03 18:52:00.925554        925554
2   2018-06-03 18:53:59.181472        181472
3   2018-06-03 18:54:00.436774        436774
4   2018-06-03 18:53:59.805276        805276
5   2018-06-03 18:52:02.325613        325613
6   2018-06-03 18:52:03.508673        508673
7   2018-06-03 18:52:07.772553        772553
8   2018-06-03 18:53:52.484954        484954
9   2018-06-03 18:53:54.733274        733274
10  2018-06-03 18:53:57.037358         37358
11  2018-06-03 18:53:58.437644        437644
12  2018-06-03 18:54:00.997659        997659
***********************************************
8 temp.json updated

8 Do you want to continue the operation (Y/N): y
                        Time  Average Rate
0   2018-06-03 18:51:57.506959        506959
1   2018-06-03 18:52:00.925554        925554
2   2018-06-03 18:53:57.037358         37358
3   2018-06-03 18:53:58.437644        437644
4   2018-06-03 18:54:00.997659        997659
5   2018-06-03 18:53:59.181472        181472
6   2018-06-03 18:54:00.436774        436774
7   2018-06-03 18:53:59.805276        805276
8   2018-06-03 18:52:02.325613        325613
9   2018-06-03 18:52:03.508673        508673
10  2018-06-03 18:52:07.772553        772553
11  2018-06-03 18:53:52.484954        484954
12  2018-06-03 18:53:54.733274        733274
13  2018-06-03 18:54:01.549498        549498
***********************************************
9 temp.json updated

9 Do you want to continue the operation (Y/N): y
                        Time  Average Rate
0   2018-06-03 18:51:57.506959        506959
1   2018-06-03 18:52:00.925554        925554
2   2018-06-03 18:52:07.772553        772553
3   2018-06-03 18:53:52.484954        484954
4   2018-06-03 18:53:54.733274        733274
5   2018-06-03 18:54:01.549498        549498
6   2018-06-03 18:53:57.037358         37358
7   2018-06-03 18:53:58.437644        437644
8   2018-06-03 18:54:00.997659        997659
9   2018-06-03 18:53:59.181472        181472
10  2018-06-03 18:54:00.436774        436774
11  2018-06-03 18:53:59.805276        805276
12  2018-06-03 18:52:02.325613        325613
13  2018-06-03 18:52:03.508673        508673
14  2018-06-03 18:54:02.061568         61568
***********************************************
10 temp.json updated

10 Do you want to continue the operation (Y/N): y
                        Time  Average Rate
0   2018-06-03 18:51:57.506959        506959
1   2018-06-03 18:52:00.925554        925554
2   2018-06-03 18:54:00.436774        436774
3   2018-06-03 18:53:59.805276        805276
4   2018-06-03 18:52:02.325613        325613
5   2018-06-03 18:52:03.508673        508673
6   2018-06-03 18:54:02.061568         61568
7   2018-06-03 18:52:07.772553        772553
8   2018-06-03 18:53:52.484954        484954
9   2018-06-03 18:53:54.733274        733274
10  2018-06-03 18:54:01.549498        549498
11  2018-06-03 18:53:57.037358         37358
12  2018-06-03 18:53:58.437644        437644
13  2018-06-03 18:54:00.997659        997659
14  2018-06-03 18:53:59.181472        181472
15  2018-06-03 18:54:03.420695        420695
***********************************************
11 temp.json updated

11 Do you want to continue the operation (Y/N): n

"Третий запуск 

(py3.6) H:\RishikeshAgrawani\Projects\Python3\Pandas>python append_data_to_json-v2-py3.py
                          Time  Average Rate
0   2018-06-03 18:51:57.506959        506959
1   2018-06-03 18:52:00.925554        925554
2   2018-06-03 18:54:01.549498        549498
3   2018-06-03 18:53:57.037358         37358
4   2018-06-03 18:53:58.437644        437644
5   2018-06-03 18:54:00.997659        997659
6   2018-06-03 18:53:59.181472        181472
7   2018-06-03 18:54:03.420695        420695
8   2018-06-03 18:54:00.436774        436774
9   2018-06-03 18:53:59.805276        805276
10  2018-06-03 18:52:02.325613        325613
11  2018-06-03 18:52:03.508673        508673
12  2018-06-03 18:54:02.061568         61568
13  2018-06-03 18:52:07.772553        772553
14  2018-06-03 18:53:52.484954        484954
15  2018-06-03 18:53:54.733274        733274
16  2018-06-03 18:55:39.415698        415698
***********************************************
1 temp.json updated

1 Do you want to continue the operation (Y/N): y
                          Time  Average Rate
0   2018-06-03 18:51:57.506959        506959
1   2018-06-03 18:52:00.925554        925554
2   2018-06-03 18:52:02.325613        325613
3   2018-06-03 18:52:03.508673        508673
4   2018-06-03 18:54:02.061568         61568
5   2018-06-03 18:52:07.772553        772553
6   2018-06-03 18:53:52.484954        484954
7   2018-06-03 18:53:54.733274        733274
8   2018-06-03 18:55:39.415698        415698
9   2018-06-03 18:54:01.549498        549498
10  2018-06-03 18:53:57.037358         37358
11  2018-06-03 18:53:58.437644        437644
12  2018-06-03 18:54:00.997659        997659
13  2018-06-03 18:53:59.181472        181472
14  2018-06-03 18:54:03.420695        420695
15  2018-06-03 18:54:00.436774        436774
16  2018-06-03 18:53:59.805276        805276
17  2018-06-03 18:55:41.861641        861641
***********************************************
2 temp.json updated

2 Do you want to continue the operation (Y/N): y
                          Time  Average Rate
0   2018-06-03 18:51:57.506959        506959
1   2018-06-03 18:52:00.925554        925554
2   2018-06-03 18:53:57.037358         37358
3   2018-06-03 18:53:58.437644        437644
4   2018-06-03 18:54:00.997659        997659
5   2018-06-03 18:53:59.181472        181472
6   2018-06-03 18:54:03.420695        420695
7   2018-06-03 18:54:00.436774        436774
8   2018-06-03 18:53:59.805276        805276
9   2018-06-03 18:55:41.861641        861641
10  2018-06-03 18:52:02.325613        325613
11  2018-06-03 18:52:03.508673        508673
12  2018-06-03 18:54:02.061568         61568
13  2018-06-03 18:52:07.772553        772553
14  2018-06-03 18:53:52.484954        484954
15  2018-06-03 18:53:54.733274        733274
16  2018-06-03 18:55:39.415698        415698
17  2018-06-03 18:54:01.549498        549498
18  2018-06-03 18:55:44.381318        381318
***********************************************
3 temp.json updated

3 Do you want to continue the operation (Y/N): y
                          Time  Average Rate
0   2018-06-03 18:51:57.506959        506959
1   2018-06-03 18:52:00.925554        925554
2   2018-06-03 18:52:02.325613        325613
3   2018-06-03 18:52:03.508673        508673
4   2018-06-03 18:54:02.061568         61568
5   2018-06-03 18:52:07.772553        772553
6   2018-06-03 18:53:52.484954        484954
7   2018-06-03 18:53:54.733274        733274
8   2018-06-03 18:55:39.415698        415698
9   2018-06-03 18:54:01.549498        549498
10  2018-06-03 18:55:44.381318        381318
11  2018-06-03 18:53:57.037358         37358
12  2018-06-03 18:53:58.437644        437644
13  2018-06-03 18:54:00.997659        997659
14  2018-06-03 18:53:59.181472        181472
15  2018-06-03 18:54:03.420695        420695
16  2018-06-03 18:54:00.436774        436774
17  2018-06-03 18:53:59.805276        805276
18  2018-06-03 18:55:41.861641        861641
19  2018-06-03 18:55:45.181318        181318
***********************************************
4 temp.json updated

4 Do you want to continue the operation (Y/N): y
                          Time  Average Rate
0   2018-06-03 18:51:57.506959        506959
1   2018-06-03 18:52:00.925554        925554
2   2018-06-03 18:55:44.381318        381318
3   2018-06-03 18:53:57.037358         37358
4   2018-06-03 18:53:58.437644        437644
5   2018-06-03 18:54:00.997659        997659
6   2018-06-03 18:53:59.181472        181472
7   2018-06-03 18:54:03.420695        420695
8   2018-06-03 18:54:00.436774        436774
9   2018-06-03 18:53:59.805276        805276
10  2018-06-03 18:55:41.861641        861641
11  2018-06-03 18:55:45.181318        181318
12  2018-06-03 18:52:02.325613        325613
13  2018-06-03 18:52:03.508673        508673
14  2018-06-03 18:54:02.061568         61568
15  2018-06-03 18:52:07.772553        772553
16  2018-06-03 18:53:52.484954        484954
17  2018-06-03 18:53:54.733274        733274
18  2018-06-03 18:55:39.415698        415698
19  2018-06-03 18:54:01.549498        549498
20  2018-06-03 18:55:45.765547        765547
***********************************************
5 temp.json updated

5 Do you want to continue the operation (Y/N): n
0 голосов
/ 03 июня 2018

Я думаю, вам следует прочитать 'temp.json' до начала цикла while в переменную df_store, если файл 'temp.json' существует.

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