Python繪制K線圖之可視化神器pyecharts的使用

更新時間：2021年03月02日 09:37:24 作者：王小王-123

這篇文章主要介紹了Python繪制K線圖之可視化神器pyecharts的使用，文中通過示例代碼介紹的非常詳細，對大家的學習或者工作具有一定的參考學習價值，需要的朋友們下面隨著小編來一起學習學習吧

K線圖

概念

股市及期貨市bai場中的K線圖的du畫法包含四個zhi數(shù)據(jù)，即開盤dao價、最高價、最低價zhuan、收盤價，所有的shuk線都是圍繞這四個數(shù)據(jù)展開，反映大勢的狀況和價格信息。如果把每日的K線圖放在一張紙上，就能得到日K線圖，同樣也可畫出周K線圖、月K線圖。研究金融的小伙伴肯定比較熟悉這個，那么我們看起來比較復雜的K線圖，又是這樣畫出來的，本文我們將一起探索K線圖的魅力與神奇之處吧！

K線圖

用處

K線圖用處于股票分析，作為數(shù)據(jù)分析，以后的進入大數(shù)據(jù)肯定是一個趨勢和熱潮，K線圖的專業(yè)知識，說實話肯定比較的復雜，這里就不做過多的展示了，有興趣的小伙伴去問問百度小哥哥喲！

K線圖系列模板

最簡單的K線圖繪制

第一個K線圖繪制，來看看需要哪些參數(shù)吧，數(shù)據(jù)集都有四個必要的喲！

import pyecharts.options as opts
from pyecharts.charts import Candlestick
 
x_data = ["2017-10-24", "2017-10-25", "2017-10-26", "2017-10-27"]
y_data = [[20, 30, 10, 35], [40, 35, 30, 55], [33, 38, 33, 40], [40, 40, 32, 42]]
 
(
 Candlestick(init_opts=opts.InitOpts(width="1200px", height="600px"))
 .add_xaxis(xaxis_data=x_data)
 .add_yaxis(series_name="", y_axis=y_data)
 .set_series_opts()
 .set_global_opts(
  yaxis_opts=opts.AxisOpts(
   splitline_opts=opts.SplitLineOpts(
    is_show=True, linestyle_opts=opts.LineStyleOpts(width=1)
   )
  )
 )
 .render("簡單K線圖.html")
)

K線圖鼠標縮放

大量的數(shù)據(jù)集的時候，我們不可以全部同時展示，我們可以縮放來進行定向展示。

from pyecharts import options as opts
from pyecharts.charts import Kline
 
data = [
 [2320.26, 2320.26, 2287.3, 2362.94],
 [2300, 2291.3, 2288.26, 2308.38],
 [2295.35, 2346.5, 2295.35, 2345.92],
 [2347.22, 2358.98, 2337.35, 2363.8],
 [2360.75, 2382.48, 2347.89, 2383.76],
 [2383.43, 2385.42, 2371.23, 2391.82],
 [2377.41, 2419.02, 2369.57, 2421.15],
 [2425.92, 2428.15, 2417.58, 2440.38],
 [2411, 2433.13, 2403.3, 2437.42],
 [2432.68, 2334.48, 2427.7, 2441.73],
 [2430.69, 2418.53, 2394.22, 2433.89],
 [2416.62, 2432.4, 2414.4, 2443.03],
 [2441.91, 2421.56, 2418.43, 2444.8],
 [2420.26, 2382.91, 2373.53, 2427.07],
 [2383.49, 2397.18, 2370.61, 2397.94],
 [2378.82, 2325.95, 2309.17, 2378.82],
 [2322.94, 2314.16, 2308.76, 2330.88],
 [2320.62, 2325.82, 2315.01, 2338.78],
 [2313.74, 2293.34, 2289.89, 2340.71],
 [2297.77, 2313.22, 2292.03, 2324.63],
 [2322.32, 2365.59, 2308.92, 2366.16],
 [2364.54, 2359.51, 2330.86, 2369.65],
 [2332.08, 2273.4, 2259.25, 2333.54],
 [2274.81, 2326.31, 2270.1, 2328.14],
 [2333.61, 2347.18, 2321.6, 2351.44],
 [2340.44, 2324.29, 2304.27, 2352.02],
 [2326.42, 2318.61, 2314.59, 2333.67],
 [2314.68, 2310.59, 2296.58, 2320.96],
 [2309.16, 2286.6, 2264.83, 2333.29],
 [2282.17, 2263.97, 2253.25, 2286.33],
 [2255.77, 2270.28, 2253.31, 2276.22],
]
 
 
c = (
 Kline()
 .add_xaxis(["2017/7/{}".format(i + 1) for i in range(31)])
 .add_yaxis(
  "kline",
  data,
  itemstyle_opts=opts.ItemStyleOpts(
   color="#ec0000",
   color0="#00da3c",
   border_color="#8A0000",
   border_color0="#008F28",
  ),
 )
 .set_global_opts(
  xaxis_opts=opts.AxisOpts(is_scale=True),
  yaxis_opts=opts.AxisOpts(
   is_scale=True,
   splitarea_opts=opts.SplitAreaOpts(
    is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
   ),
  ),
  datazoom_opts=[opts.DataZoomOpts(type_="inside")],
  title_opts=opts.TitleOpts(title="Kline-ItemStyle"),
 )
 .render("K線圖鼠標縮放.html")
)

有刻度標簽的K線圖

我們知道一個數(shù)據(jù)節(jié)點，但是我們不能在圖像里面一眼看出有哪些數(shù)據(jù)量超出了它的范圍，刻度標簽就可以派上用場了。

from pyecharts import options as opts
from pyecharts.charts import Kline
 
data = [
 [2320.26, 2320.26, 2287.3, 2362.94],
 [2300, 2291.3, 2288.26, 2308.38],
 [2295.35, 2346.5, 2295.35, 2345.92],
 [2347.22, 2358.98, 2337.35, 2363.8],
 [2360.75, 2382.48, 2347.89, 2383.76],
 [2383.43, 2385.42, 2371.23, 2391.82],
 [2377.41, 2419.02, 2369.57, 2421.15],
 [2425.92, 2428.15, 2417.58, 2440.38],
 [2411, 2433.13, 2403.3, 2437.42],
 [2432.68, 2334.48, 2427.7, 2441.73],
 [2430.69, 2418.53, 2394.22, 2433.89],
 [2416.62, 2432.4, 2414.4, 2443.03],
 [2441.91, 2421.56, 2418.43, 2444.8],
 [2420.26, 2382.91, 2373.53, 2427.07],
 [2383.49, 2397.18, 2370.61, 2397.94],
 [2378.82, 2325.95, 2309.17, 2378.82],
 [2322.94, 2314.16, 2308.76, 2330.88],
 [2320.62, 2325.82, 2315.01, 2338.78],
 [2313.74, 2293.34, 2289.89, 2340.71],
 [2297.77, 2313.22, 2292.03, 2324.63],
 [2322.32, 2365.59, 2308.92, 2366.16],
 [2364.54, 2359.51, 2330.86, 2369.65],
 [2332.08, 2273.4, 2259.25, 2333.54],
 [2274.81, 2326.31, 2270.1, 2328.14],
 [2333.61, 2347.18, 2321.6, 2351.44],
 [2340.44, 2324.29, 2304.27, 2352.02],
 [2326.42, 2318.61, 2314.59, 2333.67],
 [2314.68, 2310.59, 2296.58, 2320.96],
 [2309.16, 2286.6, 2264.83, 2333.29],
 [2282.17, 2263.97, 2253.25, 2286.33],
 [2255.77, 2270.28, 2253.31, 2276.22],
]
 
c = (
 Kline()
 .add_xaxis(["2017/7/{}".format(i + 1) for i in range(31)])
 .add_yaxis(
  "kline",
  data,
  markline_opts=opts.MarkLineOpts(
   data=[opts.MarkLineItem(type_="max", value_dim="close")]
  ),
 )
 .set_global_opts(
  xaxis_opts=opts.AxisOpts(is_scale=True),
  yaxis_opts=opts.AxisOpts(
   is_scale=True,
   splitarea_opts=opts.SplitAreaOpts(
    is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
   ),
  ),
  title_opts=opts.TitleOpts(title="標題"),
 )
 .render("刻度標簽.html")
)

K線圖鼠標無縮放

前面的是一個有縮放功能的圖例代碼，但是有時候我們不想要那么修改一下參數(shù)就可以了。

from pyecharts import options as opts
from pyecharts.charts import Kline
 
data = [
 [2320.26, 2320.26, 2287.3, 2362.94],
 [2300, 2291.3, 2288.26, 2308.38],
 [2295.35, 2346.5, 2295.35, 2345.92],
 [2347.22, 2358.98, 2337.35, 2363.8],
 [2360.75, 2382.48, 2347.89, 2383.76],
 [2383.43, 2385.42, 2371.23, 2391.82],
 [2377.41, 2419.02, 2369.57, 2421.15],
 [2425.92, 2428.15, 2417.58, 2440.38],
 [2411, 2433.13, 2403.3, 2437.42],
 [2432.68, 2334.48, 2427.7, 2441.73],
 [2430.69, 2418.53, 2394.22, 2433.89],
 [2416.62, 2432.4, 2414.4, 2443.03],
 [2441.91, 2421.56, 2418.43, 2444.8],
 [2420.26, 2382.91, 2373.53, 2427.07],
 [2383.49, 2397.18, 2370.61, 2397.94],
 [2378.82, 2325.95, 2309.17, 2378.82],
 [2322.94, 2314.16, 2308.76, 2330.88],
 [2320.62, 2325.82, 2315.01, 2338.78],
 [2313.74, 2293.34, 2289.89, 2340.71],
 [2297.77, 2313.22, 2292.03, 2324.63],
 [2322.32, 2365.59, 2308.92, 2366.16],
 [2364.54, 2359.51, 2330.86, 2369.65],
 [2332.08, 2273.4, 2259.25, 2333.54],
 [2274.81, 2326.31, 2270.1, 2328.14],
 [2333.61, 2347.18, 2321.6, 2351.44],
 [2340.44, 2324.29, 2304.27, 2352.02],
 [2326.42, 2318.61, 2314.59, 2333.67],
 [2314.68, 2310.59, 2296.58, 2320.96],
 [2309.16, 2286.6, 2264.83, 2333.29],
 [2282.17, 2263.97, 2253.25, 2286.33],
 [2255.77, 2270.28, 2253.31, 2276.22],
]
 
 
c = (
 Kline()
 .add_xaxis(["2017/7/{}".format(i + 1) for i in range(31)])
 .add_yaxis("kline", data)
 .set_global_opts(
  yaxis_opts=opts.AxisOpts(is_scale=True),
  xaxis_opts=opts.AxisOpts(is_scale=True),
  title_opts=opts.TitleOpts(title="Kline-基本示例"),
 )
 .render("鼠標無縮放.html")
)

大量數(shù)據(jù)K線圖繪制（X軸鼠標可移動）

雖然有時候縮放可以容納較多的數(shù)據(jù)量，但是還是不夠智能，可以利用這個

from pyecharts import options as opts
from pyecharts.charts import Kline
 
data = [
 [2320.26, 2320.26, 2287.3, 2362.94],
 [2300, 2291.3, 2288.26, 2308.38],
 [2295.35, 2346.5, 2295.35, 2345.92],
 [2347.22, 2358.98, 2337.35, 2363.8],
 [2360.75, 2382.48, 2347.89, 2383.76],
 [2383.43, 2385.42, 2371.23, 2391.82],
 [2377.41, 2419.02, 2369.57, 2421.15],
 [2425.92, 2428.15, 2417.58, 2440.38],
 [2411, 2433.13, 2403.3, 2437.42],
 [2432.68, 2334.48, 2427.7, 2441.73],
 [2430.69, 2418.53, 2394.22, 2433.89],
 [2416.62, 2432.4, 2414.4, 2443.03],
 [2441.91, 2421.56, 2418.43, 2444.8],
 [2420.26, 2382.91, 2373.53, 2427.07],
 [2383.49, 2397.18, 2370.61, 2397.94],
 [2378.82, 2325.95, 2309.17, 2378.82],
 [2322.94, 2314.16, 2308.76, 2330.88],
 [2320.62, 2325.82, 2315.01, 2338.78],
 [2313.74, 2293.34, 2289.89, 2340.71],
 [2297.77, 2313.22, 2292.03, 2324.63],
 [2322.32, 2365.59, 2308.92, 2366.16],
 [2364.54, 2359.51, 2330.86, 2369.65],
 [2332.08, 2273.4, 2259.25, 2333.54],
 [2274.81, 2326.31, 2270.1, 2328.14],
 [2333.61, 2347.18, 2321.6, 2351.44],
 [2340.44, 2324.29, 2304.27, 2352.02],
 [2326.42, 2318.61, 2314.59, 2333.67],
 [2314.68, 2310.59, 2296.58, 2320.96],
 [2309.16, 2286.6, 2264.83, 2333.29],
 [2282.17, 2263.97, 2253.25, 2286.33],
 [2255.77, 2270.28, 2253.31, 2276.22],
]
 
c = (
 Kline()
 .add_xaxis(["2017/7/{}".format(i + 1) for i in range(31)])
 .add_yaxis("kline", data)
 .set_global_opts(
  xaxis_opts=opts.AxisOpts(is_scale=True),
  yaxis_opts=opts.AxisOpts(
   is_scale=True,
   splitarea_opts=opts.SplitAreaOpts(
    is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
   ),
  ),
  datazoom_opts=[opts.DataZoomOpts(pos_bottom="-2%")],
  title_opts=opts.TitleOpts(title="Kline-DataZoom-slider-Position"),
 )
 .render("大量數(shù)據(jù)展示.html")
)