由 API 填充的兩個 Pandas DataFrame。需要加入特定格式的 DataFrame。
當前狀態- 兩個數據幀,每個數據幀都按時間戳索引
eth_df:
close symbol
timestamp
1541376000000 206.814430 eth
1541462400000 209.108877 eth
btc_df:
close symbol
timestamp
1541376000000 6351.06194 btc
1541462400000 6415.443409 btc
所需狀態- 按時間戳索引和按符號多索引列
portfolio_df:
eth btc
close close
timestamp
1541376000000 206.814430 6351.06194
1541462400000 209.108877 6415.443409
編輯 1:來自社區的請求:請您將 eth_df.to_dict() 和 btc_df.to_dict() 的結果添加到問題中嗎?
這是兩者的代碼和結果:
btc = cg.get_coin_market_chart_range_by_id('bitcoin','usd', start_date, end_date)
portfolio_df = pd.DataFrame(data=btc['prices'], columns=['timestamp','close'])
portfolio_df['symbol'] = 'btc'
portfolio_df = portfolio_df.set_index('timestamp')
portfolio_df.to_dict()
{'close': {1541376000000: 6351.061941056285,
1541462400000: 6415.443408541094,
1541548800000: 6474.847290336688,
show more (open the raw output data in a text editor) ...
1627344000000: 'btc',
1627430400000: 'btc',
1627516800000: 'btc',
1627603200000: 'btc',
1627689600000: 'btc',
...}}
eth = cg.get_coin_market_chart_range_by_id('ethereum','usd', start_date, end_date)
eth_df = pd.DataFrame(data=eth['prices'], columns=['timestamp','close'])
eth_df['symbol'] = 'eth'
eth_df = eth_df.set_index('timestamp')
eth_df.to_dict()
{'close': {1541376000000: 206.8144295995958,
1541462400000: 209.10887661978714,
1541548800000: 219.16088708430863,
show more (open the raw output data in a text editor) ...
1627344000000: 'eth',
1627430400000: 'eth',
1627516800000: 'eth',
...}}
btc = cg.get_coin_market_chart_range_by_id('bitcoin','usd', start_date, end_date)
我對 CoinGeckoAPI 不是很熟悉,因此假設您獲得如下所示的數據框,您無需先設置索引:
from pycoingecko import CoinGeckoAPI
from datetime import datetime
cg = CoinGeckoAPI()
start_date, end_date = 1497484800,1499138400
btc = cg.get_coin_market_chart_range_by_id('bitcoin','usd', start_date, end_date)
btc_df = pd.DataFrame(data=btc['prices'], columns=['timestamp','close'])
btc_df['symbol'] = 'btc'
eth = cg.get_coin_market_chart_range_by_id('ethereum','usd', start_date, end_date)
eth_df = pd.DataFrame(data=eth['prices'], columns=['timestamp','close'])
eth_df['symbol'] = 'eth'
您連接數據幀並進行透視:
portfolio_df = pd.concat([btc_df,eth_df]).pivot_table(index="timestamp",columns="symbol")
然後交換級別:
portfolio_df = portfolio_df.swaplevel(axis=1)
portfolio_df
symbol btc eth
close close
timestamp
1497484800000 2444.493712 346.369070
1497571200000 2513.810348 358.284517
1497657600000 2683.571344 372.357011
1497744000000 2577.219361 359.438712
1497830400000 2620.136451 362.044289
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