我的悬停注释为什么显示 NaN 而不是我的数值？

huangapple
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英文:

Why do my hover annotations have NaN instead of my values?

问题

代码部分不需要翻译。以下是您提供的代码的翻译部分：

  1. import yfinance as yf
  2. import mplfinance as mpf
  3. import matplotlib.pyplot as plt
  4. import matplotlib.patches as mpatches
  5. import pandas as pd
  6. import numpy as np
  8. # 获取股票数据的日期范围
  9. start_date = "2020-01-01"
  10. end_date = "2023-06-15"
  12. # 获取特斯拉股票数据
  13. tesla_data = yf.download("TSLA", start=start_date, end=end_date)
  14. tesla_weekly_data = tesla_data.resample("W").agg({"Open": "first", "High": "max", "Low": "min", "Close": "last", "Volume": "sum"}).dropna()
  16. # 获取最新的收盘价
  17. latest_price = tesla_weekly_data['Close'][-1]
  19. # 创建额外的图表
  20. close_price = tesla_weekly_data['Close']
  21. apd = mpf.make_addplot(close_price, color='cyan', width=2)
  23. # 绘制蜡烛图
  24. fig, axes = mpf.plot(tesla_weekly_data,
  25.                      type='candle',
  26.                      addplot=apd,
  27.                      style='yahoo',
  28.                      title='特斯拉股票价格',
  29.                      ylabel='价格',
  30.                      xlabel='日期',
  31.                      volume=True,
  32.                      ylabel_lower='成交量',
  33.                      volume_panel=1,
  34.                      figsize=(16, 8),
  35.                      returnfig=True
  36.                      )
  38. # 将y轴标签移到左侧
  39. axes[0].yaxis.tick_left()
  40. axes[1].yaxis.tick_left()
  42. # 调整价格y轴标签的位置
  43. axes[0].yaxis.set_label_coords(-0.08, 0.5)
  45. # 调整成交量y轴标签的位置
  46. axes[1].yaxis.set_label_coords(-0.08, 0.5)
  48. # 设置价格和成交量的y轴标签
  49. axes[0].set_ylabel('价格', rotation=0, labelpad=20)
  50. axes[1].set_ylabel('成交量', rotation=0, labelpad=20)
  52. # 创建图例框
  53. handles = axes[0].get_legend_handles_labels()[0]
  54. red_patch = mpatches.Patch(color='red')
  55. green_patch = mpatches.Patch(color='green')
  56. cyan_patch = mpatches.Patch(color='cyan')
  57. handles = handles[:2] + [red_patch, green_patch, cyan_patch]
  58. labels = ["涨价", "跌价", "收盘价"]
  59. axes[0].legend(handles=handles, labels=labels)
  61. # 添加一个框以显示当前价格
  62. latest_price_text = f"当前价格: ${latest_price:.2f}"
  63. box_props = dict(boxstyle='round', facecolor='white', edgecolor='black', alpha=0.8)
  64. axes[0].text(0.02, 0.95, latest_price_text, transform=axes[0].transAxes, fontsize=12, verticalalignment='top', bbox=box_props)
  66. # 定义悬停标签格式
  67. hover_label_format = [
  68.     ("开盘价: ", lambda x: f"${x:.2f}"),
  69.     ("最高价: ", lambda x: f"${x:.2f}"),
  70.     ("最低价: ", lambda x: f"${x:.2f}"),
  71.     ("收盘价: ", lambda x: f"${x:.2f}"),
  72.     ("成交量: ", lambda x: f"{int(x):,}"),
  73. ]
  75. # 创建悬停注释的函数
  76. def hover_annotations(data):
  77.     annot = pd.DataFrame(index=data.index, columns=data.columns)
  78.     annot_visible = False
  80.     texts = []
  82.     def onmove(event):
  83.         nonlocal annot_visible
  85.         if event.inaxes == axes[0]:
  86.             index = int(event.xdata)
  87.             if index >= len(data.index):
  88.                 return
  90.             values = data.iloc[index]
  91.             for label, formatter in hover_label_format:
  92.                 value = values[label.rstrip(': ')]
  93.                 if np.isnan(value):
  94.                     annot.iloc[index][label.rstrip(': ')] = ""
  95.                 else:
  96.                     annot.iloc[index][label.rstrip(': ')] = f"{label}{formatter(value)}"
  98.             annot_visible = True
  99.         else:
  100.             annot_visible = False
  102.         for t, text, (x, y) in zip(texts, annot.values, zip([event.xdata] or [], [event.ydata] or [])):
  103.             if isinstance(x, (list, np.ndarray)):
  104.                 x = x[0] if len(x) > 0 and not np.isnan(x[0]) else None
  105.             if isinstance(y, (list, np.ndarray)):
  106.                 y = y[0] if len(y) > 0 and not np.isnan(y[0]) else None
  108.             if x is not None and y is not None:
  109.                 t.set_position((x, y))
  110.                 t.set_text('\n'.join(map(str, text)))
  111.                 t.set_visible(annot_visible)
  113.         fig.canvas.draw_idle()
  115.     for _ in data.index:
  116.         t = axes[0].text(0, 0, '', visible=False, ha='left', va='top')
  117.         texts.append(t)
  119.     fig.canvas.mpl_connect('motion_notify_event', onmove)
  121.     return annot
  123. # 将悬停注释附加到图表
  124. annotations = hover_annotations(tesla_weekly_data)
  126. # 显示图表
  127. plt.show()

如果您运行此代码，它将绘制特斯拉股票的蜡烛图，并提供悬停功能，以显示开盘价、最高价、最低价、收盘价和成交量的信息。

英文: 
  1. import yfinance as yf
  2. import mplfinance as mpf
  3. import matplotlib.pyplot as plt
  4. import matplotlib.patches as mpatches
  5. import pandas as pd
  6. import numpy as np
  7. # Dates to get stock data
  8. start_date = "2020-01-01"
  9. end_date = "2023-06-15"
  10. # Fetch Tesla stock data
  11. tesla_data = yf.download("TSLA", start=start_date, end=end_date)
  12. tesla_weekly_data = tesla_data.resample("W").agg({"Open": "first", "High": "max", "Low": "min", "Close": "last", "Volume": "sum"}).dropna()
  13. # Get the latest closing price
  14. latest_price = tesla_weekly_data['Close'][-1]
  15. # Create additional plot
  16. close_price = tesla_weekly_data['Close']
  17. apd = mpf.make_addplot(close_price, color='cyan', width=2)
  18. # Plot the candlestick chart
  19. fig, axes = mpf.plot(tesla_weekly_data,
  20. type='candle',
  21. addplot=apd,
  22. style='yahoo',
  23. title='Tesla Stock Prices',
  24. ylabel='Price',
  25. xlabel='Date',
  26. volume=True,
  27. ylabel_lower='Volume',
  28. volume_panel=1,
  29. figsize=(16, 8),
  30. returnfig=True
  31. )
  32. # Move the y-axis labels to the left side
  33. axes[0].yaxis.tick_left()
  34. axes[1].yaxis.tick_left()
  35. # Adjust the position of the y-axis label for price
  36. axes[0].yaxis.set_label_coords(-0.08, 0.5)
  37. # Adjust the position of the y-axis label for volume
  38. axes[1].yaxis.set_label_coords(-0.08, 0.5)
  39. # Set y-axis label for price and volume
  40. axes[0].set_ylabel('Price', rotation=0, labelpad=20)
  41. axes[1].set_ylabel('Volume', rotation=0, labelpad=20)
  42. # Make the legend box
  43. handles = axes[0].get_legend_handles_labels()[0]
  44. red_patch = mpatches.Patch(color='red')
  45. green_patch = mpatches.Patch(color='green')
  46. cyan_patch = mpatches.Patch(color='cyan')
  47. handles = handles[:2] + [red_patch, green_patch, cyan_patch]
  48. labels = ["Price Up", "Price Down", "Closing Price"]
  49. axes[0].legend(handles=handles, labels=labels)
  50. # Add a box to display the current price
  51. latest_price_text = f"Current Price: ${latest_price:.2f}"
  52. box_props = dict(boxstyle='round', facecolor='white', edgecolor='black', alpha=0.8)
  53. axes[0].text(0.02, 0.95, latest_price_text, transform=axes[0].transAxes, fontsize=12, verticalalignment='top', bbox=box_props)
  54. # Define hover label format
  55. hover_label_format = [
  56. ("Open: ", lambda x: f"${x:.2f}"),
  57. ("High: ", lambda x: f"${x:.2f}"),
  58. ("Low: ", lambda x: f"${x:.2f}"),
  59. ("Close: ", lambda x: f"${x:.2f}"),
  60. ("Volume: ", lambda x: f"{int(x):,}"),
  61. ]
  62. # Function to create hover annotations
  63. def hover_annotations(data):
  64. annot = pd.DataFrame(index=data.index, columns=data.columns)
  65. annot_visible = False
  66. texts = []
  67. def onmove(event):
  68. nonlocal annot_visible
  69. if event.inaxes == axes[0]:
  70. index = int(event.xdata)
  71. if index >= len(data.index):
  72. return
  73. values = data.iloc[index]
  74. for label, formatter in hover_label_format:
  75. value = values[label.rstrip(': ')]
  76. if np.isnan(value):
  77. annot.iloc[index][label.rstrip(': ')] = ""
  78. else:
  79. annot.iloc[index][label.rstrip(': ')] = f"{label}{formatter(value)}"
  80. annot_visible = True
  81. else:
  82. annot_visible = False
  83. for t, text, (x, y) in zip(texts, annot.values, zip([event.xdata] or [], [event.ydata] or [])):
  84. if isinstance(x, (list, np.ndarray)):
  85. x = x[0] if len(x) > 0 and not np.isnan(x[0]) else None
  86. if isinstance(y, (list, np.ndarray)):
  87. y = y[0] if len(y) > 0 and not np.isnan(y[0]) else None
  88. if x is not None and y is not None:
  89. t.set_position((x, y))
  90. t.set_text('\n'.join(map(str, text)))
  91. t.set_visible(annot_visible)
  92. fig.canvas.draw_idle()
  93. for _ in data.index:
  94. t = axes[0].text(0, 0, '', visible=False, ha='left', va='top')
  95. texts.append(t)
  96. fig.canvas.mpl_connect('motion_notify_event', onmove)
  97. return annot
  98. # Attach hover annotations to the plot
  99. annotations = hover_annotations(tesla_weekly_data)
  100. # Display the chart
  101. plt.show()

If you run the code, instead of showing open high, low, close, and volume, its showing an error.

我的悬停注释为什么显示 NaN 而不是我的数值？

答案1

得分: 1

我稍微简化了你的代码。以下对我有效：

  1. import yfinance as yf
  2. import mplfinance as mpf
  3. import matplotlib.pyplot as plt
  4. import matplotlib.patches as mpatches
  5. import pandas as pd
  6. import numpy as np
  8. # 获取股票数据的日期
  9. start_date = "2020-01-01"
  10. end_date = "2023-06-15"
  12. # 获取特斯拉股票数据
  13. tesla_data = yf.download("TSLA", start=start_date, end=end_date)
  14. tesla_weekly_data = tesla_data.resample("W").agg(
  15.         {"Open": "first", "High": "max", "Low": "min", "Close": "last", "Volume": "sum"}
  16.     ).dropna()
  18. # 获取最新的收盘价
  19. latest_price = tesla_weekly_data['Close'][-1]
  21. # 创建附加的绘图
  22. close_price = tesla_weekly_data['Close']
  23. apd = mpf.make_addplot(close_price, color='cyan', width=2)
  25. # 绘制蜡烛图
  26. fig, axes = mpf.plot(tesla_weekly_data,
  27.                      type='candle',
  28.                      addplot=apd,
  29.                      style='yahoo',
  30.                      title='特斯拉股票价格',
  31.                      ylabel='价格',
  32.                      xlabel='日期',
  33.                      volume=True,
  34.                      ylabel_lower='交易量',
  35.                      volume_panel=1,
  36.                      figsize=(16, 8),
  37.                      returnfig=True
  38.                      )
  40. # 将y轴标签移动到左侧
  41. axes[0].yaxis.tick_left()
  42. axes[1].yaxis.tick_left()
  44. # 调整价格y轴标签的位置
  45. axes[0].yaxis.set_label_coords(-0.08, 0.5)
  47. # 调整交易量y轴标签的位置
  48. axes[1].yaxis.set_label_coords(-0.08, 0.5)
  50. # 设置价格和交易量的y轴标签
  51. axes[0].set_ylabel('价格', rotation=0, labelpad=20)
  52. axes[1].set_ylabel('交易量', rotation=0, labelpad=20)
  54. # 创建图例框
  55. handles = axes[0].get_legend_handles_labels()[0]
  56. red_patch = mpatches.Patch(color='red')
  57. green_patch = mpatches.Patch(color='green')
  58. cyan_patch = mpatches.Patch(color='cyan')
  59. handles = handles[:2] + [red_patch, green_patch, cyan_patch]
  60. labels = ["涨价", "跌价", "收盘价"]
  61. axes[0].legend(handles=handles, labels=labels)
  63. # 添加框以显示当前价格
  64. latest_price_text = f"当前价格: ${latest_price:.2f}"
  65. box_props = dict(boxstyle='round', facecolor='white', edgecolor='black', alpha=0.8)
  66. axes[0].text(0.02, 0.95, latest_price_text, transform=axes[0].transAxes,
  67.              fontsize=12, verticalalignment='top', bbox=box_props)
  69. # 创建悬停注释的函数
  70. def hover_annotations(data):
  72.     annot_visible = False
  73.     annot = axes[0].text(0, 0, '', visible=False, ha='left', va='top')
  75.     def onmove(event):
  76.         nonlocal annot_visible
  77.         nonlocal annot
  79.         if event.inaxes == axes[0]:
  80.             index = int(event.xdata)
  81.             if index >= len(data.index):
  82.                 index = -1
  83.             elif index < 0:
  84.                 index = 0
  85.             values = data.iloc[index]
  86.             mytext = (f"{values.name.date().strftime('%m/%d/%Y')}\\n"+
  87.                       f"O: {values['Open']:.2f}\\n"+
  88.                       f"H: {values['High']:.2f}\\n"+
  89.                       f"L: {values['Low']:.2f}\\n"+
  90.                       f"C: {values['Close']:.2f}\\n"+
  91.                       f"V: {values['Volume']:.0f}")
  93.             annot_visible = True
  94.         else:
  95.             mytext = ''
  96.             annot_visible = False
  98.         annot.set_position((event.xdata,event.ydata))
  99.         annot.set_text(mytext)
  100.         annot.set_visible(annot_visible)
  101.         fig.canvas.draw_idle()
  103.     fig.canvas.mpl_connect('motion_notify_event', onmove)
  105.     return annot
  108. # 将悬停注释附加到图表
  109. annotations = hover_annotations(tesla_weekly_data)
  111. # 显示图表
  112. plt.show()
英文:

I've simplified your code a little bit. The following works for me:

  1. import yfinance as yf
  2. import mplfinance as mpf
  3. import matplotlib.pyplot as plt
  4. import matplotlib.patches as mpatches
  5. import pandas as pd
  6. import numpy as np
  8. # Dates to get stock data
  9. start_date = &quot;2020-01-01&quot;
  10. end_date = &quot;2023-06-15&quot;
  12. # Fetch Tesla stock data
  13. tesla_data = yf.download(&quot;TSLA&quot;, start=start_date, end=end_date)
  14. tesla_weekly_data = tesla_data.resample(&quot;W&quot;).agg(
  15.         {&quot;Open&quot;: &quot;first&quot;, &quot;High&quot;: &quot;max&quot;, &quot;Low&quot;: &quot;min&quot;, &quot;Close&quot;: &quot;last&quot;, &quot;Volume&quot;: &quot;sum&quot;}
  16.     ).dropna()
  18. # Get the latest closing price
  19. latest_price = tesla_weekly_data[&#39;Close&#39;][-1]
  21. # Create additional plot
  22. close_price = tesla_weekly_data[&#39;Close&#39;]
  23. apd = mpf.make_addplot(close_price, color=&#39;cyan&#39;, width=2)
  25. # Plot the candlestick chart
  26. fig, axes = mpf.plot(tesla_weekly_data,
  27.                      type=&#39;candle&#39;,
  28.                      addplot=apd,
  29.                      style=&#39;yahoo&#39;,
  30.                      title=&#39;Tesla Stock Prices&#39;,
  31.                      ylabel=&#39;Price&#39;,
  32.                      xlabel=&#39;Date&#39;,
  33.                      volume=True,
  34.                      ylabel_lower=&#39;Volume&#39;,
  35.                      volume_panel=1,
  36.                      figsize=(16, 8),
  37.                      returnfig=True
  38.                      )
  40. # Move the y-axis labels to the left side
  41. axes[0].yaxis.tick_left()
  42. axes[1].yaxis.tick_left()
  44. # Adjust the position of the y-axis label for price
  45. axes[0].yaxis.set_label_coords(-0.08, 0.5)
  47. # Adjust the position of the y-axis label for volume
  48. axes[1].yaxis.set_label_coords(-0.08, 0.5)
  50. # Set y-axis label for price and volume
  51. axes[0].set_ylabel(&#39;Price&#39;, rotation=0, labelpad=20)
  52. axes[1].set_ylabel(&#39;Volume&#39;, rotation=0, labelpad=20)
  54. # Make the legend box
  55. handles = axes[0].get_legend_handles_labels()[0]
  56. red_patch = mpatches.Patch(color=&#39;red&#39;)
  57. green_patch = mpatches.Patch(color=&#39;green&#39;)
  58. cyan_patch = mpatches.Patch(color=&#39;cyan&#39;)
  59. handles = handles[:2] + [red_patch, green_patch, cyan_patch]
  60. labels = [&quot;Price Up&quot;, &quot;Price Down&quot;, &quot;Closing Price&quot;]
  61. axes[0].legend(handles=handles, labels=labels)
  63. # Add a box to display the current price
  64. latest_price_text = f&quot;Current Price: ${latest_price:.2f}&quot;
  65. box_props = dict(boxstyle=&#39;round&#39;, facecolor=&#39;white&#39;, edgecolor=&#39;black&#39;, alpha=0.8)
  66. axes[0].text(0.02, 0.95, latest_price_text, transform=axes[0].transAxes,
  67.              fontsize=12, verticalalignment=&#39;top&#39;, bbox=box_props)
  69. # Function to create hover annotations
  70. def hover_annotations(data):
  72.     annot_visible = False
  73.     annot = axes[0].text(0, 0, &#39;&#39;, visible=False, ha=&#39;left&#39;, va=&#39;top&#39;)
  75.     def onmove(event):
  76.         nonlocal annot_visible
  77.         nonlocal annot
  79.         if event.inaxes == axes[0]:
  80.             index = int(event.xdata)
  81.             if index &gt;= len(data.index):
  82.                 index = -1
  83.             elif index &lt; 0:
  84.                 index = 0
  85.             values = data.iloc[index]
  86.             mytext = (f&quot;{values.name.date().strftime(&#39;%m/%d/%Y&#39;):}\n&quot;+
  87.                       f&quot;O: {values[&#39;Open&#39;]:.2f}\n&quot;+
  88.                       f&quot;H: {values[&#39;High&#39;]:.2f}\n&quot;+
  89.                       f&quot;L: {values[&#39;Low&#39;]:.2f}\n&quot;+
  90.                       f&quot;C: {values[&#39;Close&#39;]:.2f}\n&quot;+
  91.                       f&quot;V: {values[&#39;Volume&#39;]:.0f}&quot;
  92.                      )
  94.             annot_visible = True
  95.         else:
  96.             mytext = &#39;&#39;
  97.             annot_visible = False
  99.         annot.set_position((event.xdata,event.ydata))
  100.         annot.set_text(mytext)
  101.         annot.set_visible(annot_visible)
  102.         fig.canvas.draw_idle()
  104.     fig.canvas.mpl_connect(&#39;motion_notify_event&#39;, onmove)
  106.     return annot
  109. # Attach hover annotations to the plot
  110. annotations = hover_annotations(tesla_weekly_data)
  112. # Display the chart
  113. plt.show()

I don't know what the problem was, but I completely got rid of the array of texts and the DataFrame annot (but I reused the name annot for a single annotation, what you were previously calling t). I also got rid of all the looping through these things, and the complicated formatting lambdas which seemed to me very unneccessary. At any rate, the above works for me.

huangapple
  • 本文由 发表于 2023年6月16日 09:32:02
  • 转载请务必保留本文链接：https://go.coder-hub.com/76486448.html
  • matplotlib
  • plot-annotations
  • python
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