Hi, I used the below code earlier to fetch historical data for a range of dates and since day historical data is not allowed beyond 2000 bars in a single request, I loop through a list of dates before concats the list that contains data frames with the historical data.

My problem is that now when I use the same code, I end up getting arbitrary data i.e. lots of date ranges are missing in between the way I have shown in the e.g. below. Can someone share why this may be happening.

def hist_data():

    dfs = []
    frm = ['2010-07-12 09:15', '2015-01-01 09:15', '2020-01-01 09:15']
    until = ['2014-12-31 15:30', '2019-12-31 15:30', '2022-11-17 15:30']

    for x, y in zip(frm, until):

        try:
            historicParam = {
                "exchange": "NSE",
                "symboltoken": tokens,
                "interval": 'ONE_DAY',
                "fromdate": x,
                "todate": y
            }
            dfs.append(pd.DataFrame(obj.getCandleData(historicParam)['data'],
                                    columns=['Date', 'Open', 'High', 'Low', 'Close', 'Volume']))

        except Exception as e:
            print(f'Historic Api failed: {e}')

        time.sleep(1)

    df = pd.concat(x for x in dfs)
    df['Date'] = df['Date'].str.split('T').str[0]

    return df

for tokens, symbols in zip(nifty_50['token'], nifty_50['symbol']):

    stock_data = hist_data()
    stock_data.to_csv(f'/Users/varadjoshi/Documents/Markets Data/Price Volume Data/Nifty 500 Stocks Data/{symbols}.csv', index=False)
    time.sleep(1)
    print(symbols)

Output:

![0729a34a-ecab-410e-a334-e00064d9ada3-image.png](/assets/uploads/files/1668689576208-0729a34a-ecab-410e-a334-e00064d9ada3-image.png) code_text
```15/12/14	70.4	72	67.9	68.6	129777
16/12/14	68	68.05	63.7	67	193654
17/12/14	66.7	67.45	60.6	64.8	172924
18/12/14	66.45	69.35	66	67.8	328438
19/12/14	69	80	68	68.4	987759
22/12/14	68.95	71.9	68	68.8	79850
23/12/14	69.1	69.5	66.3	67.25	48193
24/12/14	66.7	68.05	65	65.45	104596
26/12/14	66.7	68	66.25	67.25	83206
29/12/14	67.65	68.4	66.8	67.2	76121
30/12/14	67.65	69.55	66	68.2	139656
31/12/14	69.4	69.7	68.2	68.95	89187
18/12/17	131	135.35	127.7	131.85	714035
19/12/17	132.8	135.9	132.05	134.8	306865
20/12/17	134	135.5	133	134.15	197805
21/12/17	134.9	139.35	133.3	136.55	550289
22/12/17	138.7	138.75	136	136.65	292362
26/12/17	151	152	140.3	141.95	2135648
27/12/17	142.9	143.5	138	138.85	694039
28/12/17	139	140.75	136.1	137.6	448845
29/12/17	137	138.6	135.1	135.75	268609
01/01/18	136	139.5	135	138.75	350672
02/01/18	139.65	139.65	135	135.95	203144
03/01/18	137	143.5	135.1	142.3	917062
04/01/18	143.8	146	143.6	144.8	569818
05/01/18	145.85	154.95	145.15	152.2	1655604
08/01/18	153	158.4	150.5	154.6	1024843
09/01/18	155.1	156	151.25	155.3	420061
10/01/18	152.2	158.9	152.2	156.8	685480
11/01/18	154.15	161.6	154.15	158.25	943735
12/01/18	158.95	174	158.3	170.5	2949954
15/01/18	173.95	190.3	173.55	185.75	2968256
16/01/18	189	189.25	170.25	172.5	1963995
17/01/18	172.9	187.9	164.25	185.15	1988863
18/01/18	187	194.9	176.7	179	2481861

Hi, I used the below code earlier to fetch historical data for a range of dates and since day historical data is not allowed beyond 2000 bars in a single request, I loop through a list of dates before concats the list that contains data frames with the historical data.

My problem is that now when I use the same code, I end up getting arbitrary data i.e. lots of date ranges are missing in between the way I have shown in the e.g. below. Can someone share why this may be happening.

def hist_data():

    dfs = []
    frm = ['2010-07-12 09:15', '2015-01-01 09:15', '2020-01-01 09:15']
    until = ['2014-12-31 15:30', '2019-12-31 15:30', '2022-11-17 15:30']

    for x, y in zip(frm, until):

        try:
            historicParam = {
                "exchange": "NSE",
                "symboltoken": tokens,
                "interval": 'ONE_DAY',
                "fromdate": x,
                "todate": y
            }
            dfs.append(pd.DataFrame(obj.getCandleData(historicParam)['data'],
                                    columns=['Date', 'Open', 'High', 'Low', 'Close', 'Volume']))

        except Exception as e:
            print(f'Historic Api failed: {e}')

        time.sleep(1)

    df = pd.concat(x for x in dfs)
    df['Date'] = df['Date'].str.split('T').str[0]

    return df

for tokens, symbols in zip(nifty_50['token'], nifty_50['symbol']):

    stock_data = hist_data()
    stock_data.to_csv(f'/Users/varadjoshi/Documents/Markets Data/Price Volume Data/Nifty 500 Stocks Data/{symbols}.csv', index=False)
    time.sleep(1)
    print(symbols)

Output:

![0729a34a-ecab-410e-a334-e00064d9ada3-image.png](/assets/uploads/files/1668689576208-0729a34a-ecab-410e-a334-e00064d9ada3-image.png) code_text
```15/12/14	70.4	72	67.9	68.6	129777
16/12/14	68	68.05	63.7	67	193654
17/12/14	66.7	67.45	60.6	64.8	172924
18/12/14	66.45	69.35	66	67.8	328438
19/12/14	69	80	68	68.4	987759
22/12/14	68.95	71.9	68	68.8	79850
23/12/14	69.1	69.5	66.3	67.25	48193
24/12/14	66.7	68.05	65	65.45	104596
26/12/14	66.7	68	66.25	67.25	83206
29/12/14	67.65	68.4	66.8	67.2	76121
30/12/14	67.65	69.55	66	68.2	139656
31/12/14	69.4	69.7	68.2	68.95	89187
18/12/17	131	135.35	127.7	131.85	714035
19/12/17	132.8	135.9	132.05	134.8	306865
20/12/17	134	135.5	133	134.15	197805
21/12/17	134.9	139.35	133.3	136.55	550289
22/12/17	138.7	138.75	136	136.65	292362
26/12/17	151	152	140.3	141.95	2135648
27/12/17	142.9	143.5	138	138.85	694039
28/12/17	139	140.75	136.1	137.6	448845
29/12/17	137	138.6	135.1	135.75	268609
01/01/18	136	139.5	135	138.75	350672
02/01/18	139.65	139.65	135	135.95	203144
03/01/18	137	143.5	135.1	142.3	917062
04/01/18	143.8	146	143.6	144.8	569818
05/01/18	145.85	154.95	145.15	152.2	1655604
08/01/18	153	158.4	150.5	154.6	1024843
09/01/18	155.1	156	151.25	155.3	420061
10/01/18	152.2	158.9	152.2	156.8	685480
11/01/18	154.15	161.6	154.15	158.25	943735
12/01/18	158.95	174	158.3	170.5	2949954
15/01/18	173.95	190.3	173.55	185.75	2968256
16/01/18	189	189.25	170.25	172.5	1963995
17/01/18	172.9	187.9	164.25	185.15	1988863
18/01/18	187	194.9	176.7	179	2481861