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clean code: reduce pep8 warnings
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‎docs/zh-cn/user-customize-map.md‎

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@@ -29,7 +29,7 @@ import pyecharts.constants as constants
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constants.CITY_NAME_PINYIN_MAP['太原'] = 'taiyuan_detail'
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```
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请注意格式：关键词是“太原”，对应的文件名是“taiyuan_detail"， 并且不加'js'后缀。下面是所有的代码
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请注意格式：关键词是“太原”，对应的文件名是"taiyuan_detail"， 并且不加'js'后缀。下面是所有的代码
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```python
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from pyecharts import Map
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map.render()
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```
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如果只是使用 render() 生成 .html 文件的话到这里就可以了。还想要在 jupyter notebook 上展示地图的话，还需要下面一个步骤。
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如果只是使用 render() 生成 .html 文件的话到这里就可以了。还想要在 jupyter-notebook 上展示地图的话，还需要下面一个步骤。
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```
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$ jupyter nbextensions install [python lib dir]/site-packages/pyecharts/templates/js/echarts
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jupyter nbextension enable <the entry point>
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```
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你可以选择性的执行下面的语句。如果你已经装了0.1.9.7在你现在的python环境，就可以跳过
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你可以选择性的执行下面的语句。如果你已经装了 0.1.9.7 在你现在的 Python 环境，就可以跳过
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```
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jupyter nbextension enable echarts/main
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```
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然后，让我们检查以下是否已经装上了。请先运行Jupyter notebook，再打开这个链接：http://localhost:8889/nbextensions/echarts/taiyuan_details.js。
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然后，让我们检查以下是否已经装上了。请先运行 Jupyter-notebook，再打开这个链接：http://localhost:8889/nbextensions/echarts/taiyuan_details.js。
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如果能下载到，那就祝贺你，成功了。否则，请检查你的步骤。
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![customize-map-2](https://github.com/chenjiandongx/pyecharts/blob/master/images/customize-map-2.png)
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## 如何把手动加的地图变成自动的
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如果用户期望pyecharts支持自己的地图，请发请求然后再发来改动。
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如果用户期望 pyecharts 支持自己的地图，请发请求然后再发来改动。

‎pyecharts/charts/bar.py‎

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#!/usr/bin/env python
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#coding=utf-8
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# coding=utf-8
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from pyecharts.base import Base
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from pyecharts.option import get_all_options
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class Bar(Base):
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"""
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<<< Bar chart >>>
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Bar chart shows different data through the height of a bar,
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which is used in rectangular coordinate with at least 1 category axis.
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"""

‎pyecharts/charts/bar3D.py‎

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opacity of gird3D item
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:param grid3d_shading:
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3D graphics coloring effect
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'color': Only show color, not affected by lighting and other factors.
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'lambert': Through the classic lambert coloring to show the light and shade.
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'realistic': Realistic rendering.
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'color':
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Only show color, not affected by lighting and other factors.
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'lambert':
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Through the classic lambert coloring to show the light and shade.
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'realistic':
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ealistic rendering.
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:param kwargs:
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:return:
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"""

‎pyecharts/charts/effectscatter.py‎

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#!/usr/bin/env python
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#coding=utf-8
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# coding=utf-8
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from pyecharts.charts.scatter import Scatter
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from pyecharts.option import get_all_options
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class EffectScatter(Scatter):
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"""
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<<< EffectScatter chart >>>
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The scatter graph with ripple animation. The special animation effect can visually highlights some data.
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The scatter graph with ripple animation.
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The special animation effect can visually highlights some data.
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"""
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def __init__(self, title="", subtitle="", **kwargs):
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super(EffectScatter, self).__init__(title, subtitle, **kwargs)

‎pyecharts/charts/funnel.py‎

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#!/usr/bin/env python
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#coding=utf-8
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# coding=utf-8
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from pyecharts.base import Base
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from pyecharts.option import get_all_options

‎pyecharts/charts/gauge.py‎

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#!/usr/bin/env python
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#coding=utf-8
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# coding=utf-8
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from pyecharts.base import Base
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class Gauge(Base):
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"""
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<<< Gauge chart >>>
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"max": _max,
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"startAngle": _start,
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"endAngle": _end,
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"data": [{"value": value, "name": attr}]
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"data": [{
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"value": value,
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"name": attr
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}]
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})
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self._legend_visualmap_colorlst(**kwargs)

‎pyecharts/charts/geo.py‎

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geo={
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"map": maptype,
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"label": {},
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"itemStyle": {"normal": {
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"areaColor": geo_normal_color,
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"borderColor": border_color},
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"emphasis": {"areaColor": geo_emphasis_color}}
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"itemStyle": {
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"normal": {
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"areaColor": geo_normal_color,
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"borderColor": border_color
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},
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"emphasis": {
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"areaColor": geo_emphasis_color
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}}
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})
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self._option.get('legend')[0].get('data').append(name)
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‎pyecharts/charts/graph.py‎

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#!/usr/bin/env python
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#coding=utf-8
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# coding=utf-8
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from pyecharts.base import Base
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from pyecharts.option import get_all_options
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class Graph(Base):
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"""
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<<< Graph chart >>>
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Graph is a diagram to represent nodes and the links connecting nodes.
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"""
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def __init__(self, title="", subtitle="", **kwargs):
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:param graph_edge_length:
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The distance between 2 nodes on edge. This distance is also affected by repulsion.
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It can be an array to represent the range of edge length.In this case edge with
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larger value will be shorter, which means two nodes are closer. And edge with smaller value will be longer.
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larger value will be shorter, which means two nodes are closer.
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And edge with smaller value will be longer.
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:param graph_gravity:
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The gravity factor enforcing nodes approach to the center.
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The nodes will be closer to the center as the value becomes larger.
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:param graph_repulsion:
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The repulsion factor between nodes. The repulsion will be stronger and the distance between 2 nodes
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becomes further as this value becomes larger.
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The repulsion factor between nodes. The repulsion will be stronger and the
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distance between 2 nodes becomes further as this value becomes larger.
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It can be an array to represent the range of repulsion.
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In this case larger value have larger repulsion and smaller value will have smaller repulsion.
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In this case larger value have larger repulsion and smaller value
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will have smaller repulsion.
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:param graph_edge_symbol:
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Symbol of two ends of edge line.
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For example: edgeSymbol: ['circle', 'arrow']
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"name": name,
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"layout": graph_layout,
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"symbol": chart['symbol'],
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"circular": {"rotateLabel": is_rotatelabel},
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"force": {"repulsion": graph_repulsion,
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"edgeLength": graph_edge_length,
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"gravity": graph_gravity},
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"circular": {
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"rotateLabel": is_rotatelabel
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},
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"force": {
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"repulsion": graph_repulsion,
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"edgeLength": graph_edge_length,
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"gravity": graph_gravity
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},
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"label": chart['label'],
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"lineStyle": chart['line_style'],
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"roam": is_roam,

‎pyecharts/charts/heatmap.py‎

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#!/usr/bin/env python
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#coding=utf-8
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# coding=utf-8
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from pyecharts.base import Base
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from pyecharts.option import get_all_options
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class HeatMap(Base):
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"""
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<<< HeatMap chart >>>
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Heat map mainly use colors to represent values, which must be used along with visualMap component.
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Heat map mainly use colors to represent values， which must be used along
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with visualMap component.
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It can be used in either rectangular coordinate or geographic coordinate.
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But the behaviour on them are quite different. Rectangular coordinate must have two catagories to use it.
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But the behaviour on them are quite different. Rectangular coordinate
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must have two catagories to use it.
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"""
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def __init__(self, title="", subtitle="", **kwargs):
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super(HeatMap, self).__init__(title, subtitle, **kwargs)

‎pyecharts/charts/kline.py‎

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#!/usr/bin/env python
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#coding=utf-8
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# coding=utf-8
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from pyecharts.base import Base
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from pyecharts.option import get_all_options
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class Kline(Base):
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"""
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<<< Kline(Candlestick) chart >>>
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Kline chart use red to imply increasing with red and decreasing with blue
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"""
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def __init__(self, title="", subtitle="", **kwargs):
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:param y_axis:
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data pf yAxis
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Data should be the two-dimensional array shown as follow. -> [[],[]]
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Every data item (each line in the example above) represents a box, which contains 4 values. They are:
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[open, close, lowest, highest] (namely: [opening value, closing value, lowest value, highest value])
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Every data item (each line in the example above) represents a box,
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which contains 4 values.
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They are: [open, close, lowest, highest]
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(namely: [opening value, closing value, lowest value, highest value])
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:param kwargs:
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:return:
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"""

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