Making a dataframe from the list of the website

You have your indentation wrong:

import requests
import pandas as pd

all_records = []
records = []
tickers = ['A','AAL','AAPL']

url_metrics = 'https://stockrow.com/api/companies/{}/financials.json?ticker={}&dimension=Q&section=Metrics'
indicators_url = 'https://stockrow.com/api/indicators.json'

# create a list from all tickers
for s in tickers:
    indicators = {i['id']: i for i in requests.get(indicators_url).json()}
    all_records = []
    for d in requests.get(url_metrics.format(s,s)).json():
        d['id'] = indicators[d['id']]['name']
        all_records.append(d)
    
    graham_number = next(d for d in all_records if 'Graham Number' in d['id'])
    earning_yield = next(d for d in all_records if 'Earnings Yield' in d['id'])
    nav = next(d for d in all_records if 'Net Current Asset Value' in d['id'])

    # extract data from all tickers list and convert to a dataframe 
    for (k1, v1), (_, v2), (_, v3)  in zip(nav.items(), earning_yield.items(), graham_number.items()):
        if k1 in ('id'):
            continue

        records.append({
            'symbol' : s,
            'date' : k1,
            'net_current_asset_value': v1,
            'earnings_yield': v2,
            'gramham_number': v3
        })
    
    
df = pd.DataFrame(records)
print(df)
df.to_csv('data.csv', index=False)

Print:

    symbol        date net_current_asset_value earnings_yield gramham_number
0        A  2020-07-31           -1320000000.0         0.0233        28.5032
1        A  2020-04-30           -1516000000.0         0.0288        27.6998
2        A  2020-01-31           -1551000000.0         0.0297        29.3613
3        A  2019-10-31           -1515000000.0         0.0448        33.9611
4        A  2019-07-31            -421000000.0         0.0486        33.9655
..     ...         ...                     ...            ...            ...
113   AAPL  2011-12-31            6144000000.0         0.0864          9.933
114   AAPL  2011-09-30            5232000000.0         0.0735         8.1677
115   AAPL  2011-06-30            9483000000.0         0.0763         7.4198
116   AAPL  2011-03-31           13570000000.0         0.0611         6.3801
117   AAPL  2010-12-31           11851000000.0         0.0564         5.5731

[118 rows x 5 columns]

And creates data.csv: