使用concat函数而不是append

Question

我正试图使用concat函数而不是append来从这段代码中产生相同的输出：

final_dataframe = pd.DataFrame(columns = my_columns)
for symbol in stocks['Ticker'][:5]:
api_url = f'https://sandbox.iexapis.com/stable/stock/{symbol}/quote?token={IEX_CLOUD_API_TOKEN}'
data = requests.get(api_url).json()
final_dataframe = final_dataframe.append(
pd.Series([symbol, 
data['latestPrice'], 
data['marketCap'], 
'N/A'], 
index = my_columns), 
ignore_index = True)

输出是这样的：

Ticker  Stock_price Market_capitalization   Number_of_shares_to_buy
0   A         144.3       42532431075                   N/A
1   AAL       17.16       11068908461                   N/A
2   AAP       210.74      12880265047                   N/A
3   AAPL      167.43      2762301276735                 N/A
4   ABBV      164.5       287271211810                  N/A

Answer 1

这不是将数据逐行附加到DataFrame的最佳策略。首先将数据收集到Python数据结构中(这里是dict列表(，然后根据该数据结构创建数据帧。

尝试：

tickers = []
for symbol in stocks['Ticker'][:5]:
api_url = f'https://sandbox.iexapis.com/stable/stock/{symbol}/quote?token={IEX_CLOUD_API_TOKEN}'
data = requests.get(api_url).json()
d = dict(zip(my_columns, [symbol, data['latestPrice'], data['marketCap'], 'N/A']))
tickers.append(d)
df = pd.DataFrame(tickers)

输出：

>>> df
Ticker  Stock_price  Market_capitalization  Number_of_shares_to_buy
0      A       144.30            42532431075                      NaN
1    AAL        17.16            11068908461                      NaN
2    AAP       210.74            12880265047                      NaN
3   AAPL       167.43          2762301276735                      NaN
4   ABBV       164.50           287271211810                      NaN