如此接近，但只有反复试验才能使您更进一步。糟糕的文档不是很好吗？
只需除以
width一天中的分钟数即可。完整的代码，供您在下面复制和粘贴，但我所做的只是更改
width = 0.5为
width =0.5/(24*60)。
import numpy as npimport matplotlib.pyplot as pltfrom matplotlib import dates, tickerimport matplotlib as mplfrom mpl_finance import candlestick_ohlcmpl.style.use('default')data = [('2017-01-02 02:00:00', '1.05155', '1.05197', '1.05155', '1.0519'), ('2017-01-02 02:01:00', '1.05209', '1.05209', '1.05177', '1.05179'), ('2017-01-02 02:02:00', '1.05177', '1.05198', '1.05177', '1.05178'), ('2017-01-02 02:03:00', '1.05188', '1.052', '1.05188', '1.052'), ('2017-01-02 02:04:00', '1.05196', '1.05204', '1.05196', '1.05203'), ('2017-01-02 02:06:00', '1.05196', '1.05204', '1.05196', '1.05204'), ('2017-01-02 02:07:00', '1.05205', '1.0521', '1.05205', '1.05209'), ('2017-01-02 02:08:00', '1.0521', '1.0521', '1.05209', '1.05209'), ('2017-01-02 02:09:00', '1.05208', '1.05209', '1.05208', '1.05209'), ('2017-01-02 02:10:00', '1.05208', '1.05211', '1.05207', '1.05209')]ohlc_data = []for line in data: ohlc_data.append((dates.datestr2num(line[0]), np.float64(line[1]), np.float64(line[2]), np.float64(line[3]), np.float64(line[4])))fig, ax1 = plt.subplots()candlestick_ohlc(ax1, ohlc_data, width = 0.5/(24*60), colorup = 'g', colordown = 'r', alpha = 0.8)ax1.xaxis.set_major_formatter(dates.DateFormatter('%d/%m/%Y %H:%M'))ax1.xaxis.set_major_locator(ticker.MaxNLocator(10))plt.xticks(rotation = 30)plt.grid()plt.xlabel('Date')plt.ylabel('Price')plt.title('Historical Data EURUSD')plt.tight_layout()plt.show()
