Python 使用Zip函数时出错，返回的结果丢失
我想从网站上刮取一些数据，所以我编写代码来创建一个包含所有记录的列表。然后，我想从所有记录中提取一些元素来创建一个数据帧 但是，缺少数据帧的一些信息。在所有数据列表中，它有2012年至2019年的信息，但数据帧只有2018年和2019年的信息。我尝试了不同的方法来解决这个问题。最后，我发现如果我不使用Zip函数，问题就不会发生，我可以知道为什么吗？如果我不使用Zip函数，我可以使用什么解决方案吗Python 使用Zip函数时出错，返回的结果丢失,python,pandas,dataframe,web-scraping,Python,Pandas,Dataframe,Web Scraping,我想从网站上刮取一些数据，所以我编写代码来创建一个包含所有记录的列表。然后，我想从所有记录中提取一些元素来创建一个数据帧 但是，缺少数据帧的一些信息。在所有数据列表中，它有2012年至2019年的信息，但数据帧只有2018年和2019年的信息。我尝试了不同的方法来解决这个问题。最后，我发现如果我不使用Zip函数，问题就不会发生，我可以知道为什么吗？如果我不使用Zip函数，我可以使用什么解决方案吗 import requests import pandas as pd records = []
import requests
import pandas as pd
records = []
tickers = ['AAL']
url_metrics = 'https://stockrow.com/api/companies/{}/financials.json?ticker={}&dimension=A§ion=Growth'
indicators_url = 'https://stockrow.com/api/indicators.json'
# scrape all data and append to a list - all_records
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)
gross_profit_growth = next(d for d in all_records if 'Gross Profit Growth' in d['id'])
operating_income_growth = next(d for d in all_records if 'Operating Income Growth' in d['id'])
net_income_growth = next(d for d in all_records if 'Net Income Growth' in d['id'])
diluted_eps_growth = next(d for d in all_records if 'EPS Growth (diluted)' in d['id'])
operating_cash_flow_growth = next(d for d in all_records if 'Operating Cash Flow Growth' in d['id'])
# extract values from all_records and create the dataframe
for (k1, v1), (_, v2), (_, v3), (_, v4), (_, v5) in zip(gross_profit_growth.items(), operating_income_growth.items(), net_income_growth.items(), diluted_eps_growth.items(), operating_cash_flow_growth.items()):
if k1 in ('id'):
continue
records.append({
'symbol' : s,
'date' : k1,
'gross_profit_growth%': v1,
'operating_income_growth%': v2,
'net_income_growth%': v3,
'diluted_eps_growth%' : v4,
'operating_cash_flow_growth%' : v5
})
df = pd.DataFrame(records)
df.head(50)
symbol date gross_profit_growth% operating_income_growth% net_income_growth% diluted_eps_growth% operating_cash_flow_growth%
0 AAL 2019-12-31 0.0405 -0.1539 -0.0112 0.2508 0.0798
1 AAL 2018-12-31 -0.0876 -0.2463 0.0 -0.2231 -0.2553
symbol date gross_profit_growth% operating_income_growth% net_income_growth% diluted_eps_growth% operating_cash_flow_growth%
0 AAL 31/12/2019 0.0405 0.154 0.1941 0.2508 0.0798
1 AAL 31/12/2018 -0.0876 -0.3723 0.1014 -0.2231 -0.2553
2 AAL 31/12/2017 -0.0165 -0.1638 -0.5039 -0.1892 -0.2728
3 AAL 31/12/2016 -0.079 -0.1844 -0.6604 -0.5655 0.044
4 AAL 31/12/2015 0.1983 0.4601 1.6405 1.8168 1.0289
5 AAL 31/12/2014 0.7305 2.0372 2.5714 1.2308 3.563
6 AAL 31/12/2013 0.3575 8.4527 0.0224 nan -0.4747
7 AAL 31/12/2012 0.1688 1.1427 0.052 nan 0.7295
8 AAL 31/12/2011 0.0588 -4.3669 -3.2017 nan -0.4013
9 AAL 31/12/2010 0.3413 1.3068 0.6792 nan 0.3344
gross_profit_growth% operating_income_growth% net_income_growth% diluted_eps_growth% operating_cash_flow_growth% symbol
2019-10-31 0.0466 0.0409 2.3892 2.4742 -0.0607 A
2018-10-31 0.1171 0.1202 -0.538 -0.5381 0.2227 A
2017-10-31 0.0919 0.3122 0.4805 0.5 0.1211 A
2016-10-31 0.0764 0.1782 0.1521 0.1765 0.5488 A
2015-10-31 0.0329 0.2458 -0.2696 -0.1905 -0.2996 A
2014-10-31 0.0362 0.0855 -0.252 -0.3 -0.3655 A
2013-10-31 -0.4709 -0.655 -0.3634 -0.3578 -0.0619 A
2012-10-31 0.0213 0.0448 0.1393 0.1474 -0.0254 A
2011-10-31 0.2044 0.8922 0.4795 0.6102 0.7549 A
2019-12-31 0.0405 0.154 0.1941 0.2508 0.0798 AAL
2018-12-31 -0.0876 -0.3723 0.1014 -0.2231 -0.2553 AAL
2017-12-31 -0.0165 -0.1638 -0.5039 -0.1892 -0.2728 AAL
2016-12-31 -0.079 -0.1844 -0.6604 -0.5655 0.044 AAL
2015-12-31 0.1983 0.4601 1.6405 1.8168 1.0289 AAL
2014-12-31 0.7305 2.0372 2.5714 1.2308 3.563 AAL
2013-12-31 0.3575 8.4527 0.0224 NaN -0.4747 AAL
2012-12-31 0.1688 1.1427 0.052 NaN 0.7295 AAL
2011-12-31 0.0588 -4.3669 -3.2017 NaN -0.4013 AAL
2010-12-31 0.3413 1.3068 0.6792 NaN 0.3344 AAL
2020-09-30 0.0667 0.0369 0.039 NaN 0.1626 AAPL
2019-09-30 -0.0338 -0.0983 -0.0718 -0.0017 -0.1039 AAPL
2018-09-30 0.1548 0.1557 0.2312 0.2932 0.2057 AAPL
2017-09-30 0.0466 0.022 0.0583 0.1083 -0.0303 AAPL
2016-09-30 -0.1 -0.1573 -0.1443 -0.0987 -0.185 AAPL
2015-09-30 0.3273 0.3567 0.3514 0.4295 0.3609 AAPL
2014-09-30 0.0969 0.0715 0.0668 0.1358 0.1127 AAPL
2013-09-30 -0.0635 -0.113 -0.1125 -0.0996 0.0553 AAPL
2012-09-30 0.567 0.6348 0.6099 0.595 0.3551 AAPL
2011-09-30 0.706 0.8379 0.8499 0.827 1.0182 AAPL
尝试使用
itertoolszip\u longest gross_profit_growth% operating_income_growth% net_income_growth% diluted_eps_growth% operating_cash_flow_growth% symbol
2019-10-31 0.0466 0.0409 2.3892 2.4742 -0.0607 A
2018-10-31 0.1171 0.1202 -0.538 -0.5381 0.2227 A
2017-10-31 0.0919 0.3122 0.4805 0.5 0.1211 A
2016-10-31 0.0764 0.1782 0.1521 0.1765 0.5488 A
2015-10-31 0.0329 0.2458 -0.2696 -0.1905 -0.2996 A
2014-10-31 0.0362 0.0855 -0.252 -0.3 -0.3655 A
2013-10-31 -0.4709 -0.655 -0.3634 -0.3578 -0.0619 A
2012-10-31 0.0213 0.0448 0.1393 0.1474 -0.0254 A
2011-10-31 0.2044 0.8922 0.4795 0.6102 0.7549 A
2019-12-31 0.0405 0.154 0.1941 0.2508 0.0798 AAL
2018-12-31 -0.0876 -0.3723 0.1014 -0.2231 -0.2553 AAL
2017-12-31 -0.0165 -0.1638 -0.5039 -0.1892 -0.2728 AAL
2016-12-31 -0.079 -0.1844 -0.6604 -0.5655 0.044 AAL
2015-12-31 0.1983 0.4601 1.6405 1.8168 1.0289 AAL
2014-12-31 0.7305 2.0372 2.5714 1.2308 3.563 AAL
2013-12-31 0.3575 8.4527 0.0224 NaN -0.4747 AAL
2012-12-31 0.1688 1.1427 0.052 NaN 0.7295 AAL
2011-12-31 0.0588 -4.3669 -3.2017 NaN -0.4013 AAL
2010-12-31 0.3413 1.3068 0.6792 NaN 0.3344 AAL
2020-09-30 0.0667 0.0369 0.039 NaN 0.1626 AAPL
2019-09-30 -0.0338 -0.0983 -0.0718 -0.0017 -0.1039 AAPL
2018-09-30 0.1548 0.1557 0.2312 0.2932 0.2057 AAPL
2017-09-30 0.0466 0.022 0.0583 0.1083 -0.0303 AAPL
2016-09-30 -0.1 -0.1573 -0.1443 -0.0987 -0.185 AAPL
2015-09-30 0.3273 0.3567 0.3514 0.4295 0.3609 AAPL
2014-09-30 0.0969 0.0715 0.0668 0.1358 0.1127 AAPL
2013-09-30 -0.0635 -0.113 -0.1125 -0.0996 0.0553 AAPL
2012-09-30 0.567 0.6348 0.6099 0.595 0.3551 AAPL
2011-09-30 0.706 0.8379 0.8499 0.827 1.0182 AAPL