当缺少某些值时，如何在烛台图表中添加带有注释的线条？
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【中文标题】当缺少某些值时，如何在烛台图表中添加带有注释的线条？【英文标题】：How to add lines with annotations to candlestick charts when some values are missing? 【发布时间】：2021-04-23 19:04:39 【问题描述】：我正在尝试使用 Plotly 在我的 OHLC 蜡烛图上叠加一个标记/折线图。
代码
import plotly.graph_objects as go
import pandas as pd
from datetime import datetime
df = pd.DataFrame(
'index': 0: 0,
1: 1,
2: 2,
3: 3,
4: 4,
5: 5,
6: 6,
7: 7,
8: 8,
9: 9,
10: 10,
11: 11,
12: 12,
13: 13,
14: 14,
15: 15,
16: 16,
17: 17,
18: 18,
19: 19,
20: 20,
21: 21,
22: 22,
23: 23,
24: 24,
'Date': 0: '2018-09-03',
1: '2018-09-04',
2: '2018-09-05',
3: '2018-09-06',
4: '2018-09-07',
5: '2018-09-10',
6: '2018-09-11',
7: '2018-09-12',
8: '2018-09-13',
9: '2018-09-14',
10: '2018-09-17',
11: '2018-09-18',
12: '2018-09-19',
13: '2018-09-20',
14: '2018-09-21',
15: '2018-09-24',
16: '2018-09-25',
17: '2018-09-26',
18: '2018-09-27',
19: '2018-09-28',
20: '2018-10-01',
21: '2018-10-02',
22: '2018-10-03',
23: '2018-10-04',
24: '2018-10-05',
'Open': 0: 1.2922067642211914,
1: 1.2867859601974487,
2: 1.2859420776367188,
3: 1.2914056777954102,
4: 1.2928247451782229,
5: 1.292808175086975,
6: 1.3027958869934082,
7: 1.3017443418502808,
8: 1.30451238155365,
9: 1.3110626935958862,
10: 1.3071041107177734,
11: 1.3146650791168213,
12: 1.3166556358337402,
13: 1.3140604496002195,
14: 1.3271400928497314,
15: 1.3080958127975464,
16: 1.3117163181304932,
17: 1.3180439472198486,
18: 1.3169677257537842,
19: 1.3077707290649414,
20: 1.3039510250091553,
21: 1.3043931722640991,
22: 1.2979763746261597,
23: 1.2941633462905884,
24: 1.3022021055221558,
'High': 0: 1.2934937477111816,
1: 1.2870012521743774,
2: 1.2979259490966797,
3: 1.2959914207458496,
4: 1.3024225234985352,
5: 1.3052103519439695,
6: 1.30804443359375,
7: 1.3044441938400269,
8: 1.3120088577270508,
9: 1.3143367767333984,
10: 1.3156682252883911,
11: 1.3171066045761108,
12: 1.3211784362792969,
13: 1.3296104669570925,
14: 1.3278449773788452,
15: 1.3166556358337402,
16: 1.3175750970840454,
17: 1.3196094036102295,
18: 1.3180439472198486,
19: 1.3090718984603882,
20: 1.3097577095031738,
21: 1.3049719333648682,
22: 1.3020155429840088,
23: 1.3036959171295166,
24: 1.310753345489502,
'Low': 0: 1.2856279611587524,
1: 1.2813942432403564,
2: 1.2793285846710205,
3: 1.289723515510559,
4: 1.2918561697006226,
5: 1.289823293685913,
6: 1.2976733446121216,
7: 1.298414707183838,
8: 1.3027619123458862,
9: 1.3073604106903076,
10: 1.3070186376571655,
11: 1.3120776414871216,
12: 1.3120431900024414,
13: 1.3140085935592651,
14: 1.305841088294983,
15: 1.3064552545547483,
16: 1.3097233772277832,
17: 1.3141123056411743,
18: 1.309706211090088,
19: 1.3002548217773438,
20: 1.3014055490493774,
21: 1.2944146394729614,
22: 1.2964619398117063,
23: 1.2924572229385376,
24: 1.3005592823028564,
'Close': 0: 1.292306900024414,
1: 1.2869019508361816,
2: 1.2858428955078125,
3: 1.2914891242980957,
4: 1.2925406694412231,
5: 1.2930254936218262,
6: 1.302643060684204,
7: 1.3015578985214231,
8: 1.304546356201172,
9: 1.311131477355957,
10: 1.307326316833496,
11: 1.3146305084228516,
12: 1.3168463706970217,
13: 1.3141123056411743,
14: 1.327087163925171,
15: 1.30804443359375,
16: 1.3117333650588991,
17: 1.3179919719696045,
18: 1.3172800540924072,
19: 1.3078734874725342,
20: 1.3039000034332275,
21: 1.3043591976165771,
22: 1.2981956005096436,
23: 1.294062852859497,
24: 1.3024225234985352,
'Pivot Price': 0: 1.2934937477111816,
1: np.nan,
2: 1.2793285846710205,
3: np.nan,
4: np.nan,
5: np.nan,
6: np.nan,
7: np.nan,
8: np.nan,
9: np.nan,
10: np.nan,
11: np.nan,
12: np.nan,
13: 1.3296104669570925,
14: np.nan,
15: np.nan,
16: np.nan,
17: np.nan,
18: np.nan,
19: np.nan,
20: np.nan,
21: np.nan,
22: np.nan,
23: 1.2924572229385376,
24: np.nan)
fig = go.Figure(data=[go.Candlestick(x=df['Date'],
open=df['Open'],
high=df['High'],
low=df['Low'],
close=df['Close'])])
fig.add_trace(
go.Scatter(mode = "lines+markers",
x=df['Date'],
y=df["Pivot Price"]
))
fig.update_layout(
autosize=False,
width=1000,
height=800,)
fig.show()
这是当前图片
这是所需的输出/图像
我想要标记（枢轴）之间的黑线。理想情况下，我还希望每条线旁边有一个值，显示每个枢轴之间的距离，但我不知道该怎么做。
例如，前两个枢轴之间的距离round(abs(1.293494 - 1.279329),3) 返回0.014，所以理想情况下我会喜欢这条线。
第二个是round(abs(1.279329 - 1.329610),3)，所以值是0.05。我已经手动编辑了图像并为前两个值添加了线条，以直观地表示我试图实现的目标。
【问题讨论】：
【参考方案1】：问题似乎是缺失值。所以只需将pandas.Series.interpolate 与fig.add_annotation 结合使用即可：
我还添加了差异注释。肯定有比for loops 更优雅的方法来做到这一点，但它确实可以完成这项工作。如果有什么不清楚的地方请告诉我！
import pandas as pd
import numpy as np
import plotly.graph_objects as go
df = pd.DataFrame(
'index': 0: 0,
1: 1,
2: 2,
3: 3,
4: 4,
5: 5,
6: 6,
7: 7,
8: 8,
9: 9,
10: 10,
11: 11,
12: 12,
13: 13,
14: 14,
15: 15,
16: 16,
17: 17,
18: 18,
19: 19,
20: 20,
21: 21,
22: 22,
23: 23,
24: 24,
'Date': 0: '2018-09-03',
1: '2018-09-04',
2: '2018-09-05',
3: '2018-09-06',
4: '2018-09-07',
5: '2018-09-10',
6: '2018-09-11',
7: '2018-09-12',
8: '2018-09-13',
9: '2018-09-14',
10: '2018-09-17',
11: '2018-09-18',
12: '2018-09-19',
13: '2018-09-20',
14: '2018-09-21',
15: '2018-09-24',
16: '2018-09-25',
17: '2018-09-26',
18: '2018-09-27',
19: '2018-09-28',
20: '2018-10-01',
21: '2018-10-02',
22: '2018-10-03',
23: '2018-10-04',
24: '2018-10-05',
'Open': 0: 1.2922067642211914,
1: 1.2867859601974487,
2: 1.2859420776367188,
3: 1.2914056777954102,
4: 1.2928247451782229,
5: 1.292808175086975,
6: 1.3027958869934082,
7: 1.3017443418502808,
8: 1.30451238155365,
9: 1.3110626935958862,
10: 1.3071041107177734,
11: 1.3146650791168213,
12: 1.3166556358337402,
13: 1.3140604496002195,
14: 1.3271400928497314,
15: 1.3080958127975464,
16: 1.3117163181304932,
17: 1.3180439472198486,
18: 1.3169677257537842,
19: 1.3077707290649414,
20: 1.3039510250091553,
21: 1.3043931722640991,
22: 1.2979763746261597,
23: 1.2941633462905884,
24: 1.3022021055221558,
'High': 0: 1.2934937477111816,
1: 1.2870012521743774,
2: 1.2979259490966797,
3: 1.2959914207458496,
4: 1.3024225234985352,
5: 1.3052103519439695,
6: 1.30804443359375,
7: 1.3044441938400269,
8: 1.3120088577270508,
9: 1.3143367767333984,
10: 1.3156682252883911,
11: 1.3171066045761108,
12: 1.3211784362792969,
13: 1.3296104669570925,
14: 1.3278449773788452,
15: 1.3166556358337402,
16: 1.3175750970840454,
17: 1.3196094036102295,
18: 1.3180439472198486,
19: 1.3090718984603882,
20: 1.3097577095031738,
21: 1.3049719333648682,
22: 1.3020155429840088,
23: 1.3036959171295166,
24: 1.310753345489502,
'Low': 0: 1.2856279611587524,
1: 1.2813942432403564,
2: 1.2793285846710205,
3: 1.289723515510559,
4: 1.2918561697006226,
5: 1.289823293685913,
6: 1.2976733446121216,
7: 1.298414707183838,
8: 1.3027619123458862,
9: 1.3073604106903076,
10: 1.3070186376571655,
11: 1.3120776414871216,
12: 1.3120431900024414,
13: 1.3140085935592651,
14: 1.305841088294983,
15: 1.3064552545547483,
16: 1.3097233772277832,
17: 1.3141123056411743,
18: 1.309706211090088,
19: 1.3002548217773438,
20: 1.3014055490493774,
21: 1.2944146394729614,
22: 1.2964619398117063,
23: 1.2924572229385376,
24: 1.3005592823028564,
'Close': 0: 1.292306900024414,
1: 1.2869019508361816,
2: 1.2858428955078125,
3: 1.2914891242980957,
4: 1.2925406694412231,
5: 1.2930254936218262,
6: 1.302643060684204,
7: 1.3015578985214231,
8: 1.304546356201172,
9: 1.311131477355957,
10: 1.307326316833496,
11: 1.3146305084228516,
12: 1.3168463706970217,
13: 1.3141123056411743,
14: 1.327087163925171,
15: 1.30804443359375,
16: 1.3117333650588991,
17: 1.3179919719696045,
18: 1.3172800540924072,
19: 1.3078734874725342,
20: 1.3039000034332275,
21: 1.3043591976165771,
22: 1.2981956005096436,
23: 1.294062852859497,
24: 1.3024225234985352,
'Pivot Price': 0: 1.2934937477111816,
1: np.nan,
2: 1.2793285846710205,
3: np.nan,
4: np.nan,
5: np.nan,
6: np.nan,
7: np.nan,
8: np.nan,
9: np.nan,
10: np.nan,
11: np.nan,
12: np.nan,
13: 1.3296104669570925,
14: np.nan,
15: np.nan,
16: np.nan,
17: np.nan,
18: np.nan,
19: np.nan,
20: np.nan,
21: np.nan,
22: np.nan,
23: 1.2924572229385376,
24: np.nan)
import plotly.graph_objects as go
import pandas as pd
from datetime import datetime
# df=pd.read_csv("for_so.csv")
fig = go.Figure(data=[go.Candlestick(x=df['Date'],
# fig = go.Figure(data=[go.Candlestick(x=df.index,
open=df['Open'],
high=df['High'],
low=df['Low'],
close=df['Close'])])
# some calculations
df_diff = df['Pivot Price'].dropna().diff().copy()
df2 = df[df.index.isin(df_diff.index)].copy()
df2['Price Diff'] = df['Pivot Price'].dropna().values
fig.add_trace(
go.Scatter(mode = "lines+markers",
x=df['Date'],
y=df["Pivot Price"]
))
fig.update_layout(
autosize=False,
width=1000,
height=800,)
fig.add_trace(go.Scatter(x=df['Date'], y=df['Pivot Price'].interpolate(),
# fig.add_trace(go.Scatter(x=df.index, y=df['Pivot Price'].interpolate(),
mode = 'lines',
line = dict(color='black')))
def annot(value):
# print(type(value))
if np.isnan(value):
return ''
else:
return value
j = 0
for i, p in enumerate(df['Pivot Price']):
# print(p)
# if not np.isnan(p) and not np.isnan(df_diff.iloc[j]):
if not np.isnan(p):
# print(not np.isnan(df_diff.iloc[j]))
fig.add_annotation(dict(font=dict(color='rgba(0,0,200,0.8)',size=12),
x=df['Date'].iloc[i],
# x=df.index[i],
# x = xStart
y=p,
showarrow=False,
text=annot(round(abs(df_diff.iloc[j]),3)),
textangle=0,
xanchor='right',
xref="x",
yref="y"))
j = j + 1
fig.update_xaxes(type='category')
fig.show()
【讨论】：
【参考方案2】：问题似乎缺少值，情节难以处理。有了这个技巧，你只能画点；
has_value = ~df["Pivot Price"].isna()
import plotly.graph_objects as go
import pandas as pd
from datetime import datetime
df=pd.read_csv("notebooks/for_so.csv")
fig = go.Figure(data=[go.Candlestick(x=df['Date'],
open=df['Open'],
high=df['High'],
low=df['Low'],
close=df['Close'])])
fig.add_trace(
go.Scatter(mode = 'lines',
x=df[has_value]['Date'],
y=df[has_value]["Pivot Price"], line='color':'black', 'width':1
))
fig.add_trace(
go.Scatter(mode = "markers",
x=df['Date'],
y=df["Pivot Price"]
))
fig.update_layout(
autosize=False,
width=1000,
height=800,)
fig.show()
这是为我做的。
【讨论】：
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