[数据可视化]绘制持仓榜单的“棒棒糖图”
1. 需求
2. Plotly
3. Dash
4. 安装
pip install plotly dash或者也可以用 conda 进行安装。
5. 数据格式和数据处理
excel_pd = pd.read_excel('data/IC期货商历史数据(1).xlsx', index_col='日期')# 去空excel_pd.dropna()# 去除000905_SH列excel_pd = excel_pd.drop(labels='000905_SH', axis=1)# 去0行excel_pd = excel_pd[~(excel_pd == 0).all(axis=1)]# 取出时间列表，获取最大日期和最小日期，为日历选项做判断date_list = excel_pd.index.values.tolist()min_date = min(date_list)max_date = max(date_list)def get_data_via_date_from_excel(date): # 筛选日期 sheet1_data = excel_pd.loc[date] # 去除列值为0 sheet1_data = sheet1_data[sheet1_data != 0] # 排序 从小到大 sheet1_data = sheet1_data.sort_values() # 空仓 short_hold = sheet1_data[sheet1_data < 0] # 多仓 long_hold = sheet1_data[sheet1_data >= 0].sort_values(ascending=False) return short_hold, long_hold6. 画图
Matplotlib画图
def draw_lollipop_graph(short_hold, long_hold, date): # sheet_major.index.values.tolist() fig, ax = plt.subplots(figsize=(10, 8)) # 空仓水平线 ax.hlines(y=[i for i in range(len(short_hold))], xmin=list(short_hold), xmax=[0] * len(short_hold.index), color='#1a68cc', label='空') # 多仓水平线 ax.hlines(y=[i for i in range(len(long_hold))], xmax=list(long_hold), xmin=[0] * len(long_hold.index), color='red', label='多') # 画散点 ax.scatter(x=list(short_hold), y=[i for i in range(len(short_hold))], s=10, marker='d', edgecolors="#1a68cc", zorder=2, color='white') # zorder设置该点覆盖线 ax.scatter(x=list(long_hold), y=[i for i in range(len(long_hold))], s=10, marker='d', edgecolors="red", zorder=2, color='white') # zorder设置该点覆盖线 # 画线两端标注图 for x, y, label in zip(list(short_hold), range(len(short_hold)), short_hold.index): plt.text(x=x, y=y, s=label+'({}) '.format(abs(x)), horizontalalignment='right', verticalalignment='center', fontsize=10) for x, y, label in zip(list(long_hold), range(len(long_hold)), long_hold.index): plt.text(x=x, y=y, s=' '+label+'({})'.format(abs(x)), horizontalalignment='left', verticalalignment='center', fontsize=10) # 设置排名 size = [17, 16, 15] + [8 for i in range(max(len(short_hold), len(long_hold))-3)] color = ['#b91818', '#e26012', '#dd9f10'] + ['#404040' for i in range(max(len(short_hold), len(long_hold))-3)] for i, s, c in zip(range(max(len(short_hold), len(long_hold))+1), size, color): plt.annotate(s=i+1, xy=(0, i), fontsize=s, ma='center', ha='center', color=c) # 坐标轴y反置 ax.invert_yaxis() # 坐标轴不可见 ax.set_xticks([]) ax.set_yticks([]) ax.spines['top'].set_visible(False) # 去上边框 ax.spines['bottom'].set_visible(False) # 去下边框 ax.spines['left'].set_visible(False) # 去左边框 ax.spines['right'].set_visible(False) # 去右边框 # 设置title ax.set_title('黄金持仓龙虎榜单({})'.format(date), position=(0.7, 1.07), fontdict=dict(fontsize=20, color='black')) # 自动获取ax图例句柄及其标签 handles, labels = ax.get_legend_handles_labels() plt.legend(handles=handles, ncol=2, bbox_to_anchor=(0.75, 1.05), labels=labels, edgecolor='white', fontsize=10) # 保存fig image_filename = "lollipop_rank.png" plt.savefig(image_filename) encoded_image = base64.b64encode(open(image_filename, 'rb').read()) # plt.show() return encoded_imagePlotly画图
import plotly.graph_objects as gofig = go.Figure() # 创建空画布fig.show()fig = go.Figure(data=[trace1, trace2]) # 定义figure时加上轨迹数据Figure.add_traces(data[, rows, cols, …]) # 或者先定义一张空的画布，再添加轨迹Figure.update_traces([patch, selector, row, …]) # 更新轨迹# 可运行代码import plotly.graph_objects as go
trace = [go.Scatter( # 创建trace x=[0, 1, 2], y=[2, 2, 2], mode="markers", marker=dict(color="#1a68cc", size=20),)]fig = go.Figure(data=trace)fig.show()import plotly.graph_objects as go
trace = [go.Scatter( x=[0, 1, 2], y=[2, 2, 2], mode="markers", marker=dict(color="#1a68cc", size=20),)]# 创建layout，添加标题layout = go.Layout( title=go.layout.Title(text="Converting Graph Objects To Dictionaries and JSON") )fig = go.Figure(data=trace, layout=layout)fig.show()Figure.update_layout([dict1, overwrite]) # 也可使用API更新图层# 空仓水平线short_shapes = [{'type': 'line', 'yref': 'y1', 'y0': k, 'y1': k, 'xref': 'x1', 'x0': 0, 'x1': i, 'layer': 'below', 'line': dict( color="#1a68cc", ), } for i, k in zip(short_hold, range(len(short_hold)))]# 多仓水平线long_shapes = [{'type': 'line', 'yref': 'y1', 'y0': k, 'y1': k, 'xref': 'x1', 'x0': j, 'x1': 0, 'layer': 'below', 'line': dict( color="red", ) } for j, k in zip(long_hold, range(len(long_hold)))]# 画散点fig.add_trace(go.Scatter( x=short_hold, y=[i for i in range(len(short_hold))], mode='markers+text', marker=dict(color="#1a68cc", symbol='diamond-open'), text=[label + '(' + str(abs(i)) + ') ' for label, i in zip(short_hold.index, short_hold)], # 散点两端的期货公司标注和持仓数 textposition='middle left', # 标注文字的位置 showlegend=False # 该轨迹不显示图例legend))
fig.add_trace(go.Scatter( x=long_hold, y=[i for i in range(len(long_hold))], mode='markers+text', text=[' ' + label + '(' + str(abs(i)) + ')' for label, i in zip(long_hold.index, long_hold)], # 散点两端的期货公司标注和持仓数 marker=dict(color='red', symbol='diamond-open'), textposition='middle right', # 标注文字的位置 showlegend=False # 该轨迹不显示图例legend))# 线上的排名顺序fig.add_trace(go.Scatter( x=[0]*max(len(short_hold), len(long_hold)), y=[i for i in range(max(len(short_hold), len(long_hold)))], mode='text', text=[str(i+1) for i in range(max(len(short_hold), len(long_hold)))], # 排名从1开始 textfont=dict(color=['#b91818', '#e26012', '#dd9f10'] + ['#404040' for i in range(max(len(short_hold), len(long_hold)) - 3)], size=[17, 16, 15] + [10 for i in range(max(len(short_hold), len(long_hold)) - 3)], family="Open Sans"), textposition='top center', showlegend=False))
# 加上这条trace只是为了显示legend图例,因为scatter图例中显示的text在plotly现有的版本基础上去除不了fig.add_trace(go.Scatter( x=[0, long_hold[0]], y=[range(len(long_hold))[0], range(len(long_hold))[0]], mode='lines', marker=dict(color='red'), name='多'))
fig.add_trace(go.Scatter( x=[0, short_hold[0]], y=[range(len(short_hold))[0], range(len(short_hold))[0]], mode='lines', marker=dict(color='#1a68cc'), name='空'))# X, Y坐标轴不可见fig.update_xaxes( showticklabels=False, showgrid=False, zeroline=False,)fig.update_yaxes( showticklabels=False, showgrid=False, zeroline=False, autorange='reversed' # Y 轴倒置)fig.update_layout(shapes=short_shapes+long_shapes, # 添加水平线 width=2100, height=900, legend=dict(x=0.62, y=1.02, orientation='h'), template="plotly_white", title=dict( text='黄金持仓龙虎榜单(' + date + ')', y=0.95, x=0.65, xanchor='center', yanchor='top', font=dict(family="Open Sans", size=30) ))7. 创建Dash 应用程序
import dashimport dash_html_components as htmlimport dash_core_components as dcc
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div([ html.Div(dcc.DatePickerSingle( id='my-date-picker-single', min_date_allowed=min_date, # 日历最小日期 max_date_allowed=max_date, # 日历最大日期 date=max_date # dash 程序初始化日历的默认值日期 ), style={"margin-left": "300px"}), html.Div(id='output-container-date-picker-single', style={"text-align": "center"})])Matplotlib + Dash 框架
@app.callback( Output('output-container-date-picker-single', 'children'), [Input('my-date-picker-single', 'date')])def update_output(date): print("date", date) if date is not None: if date not in date_list: return html.Div([ "数据不存在" ]) encoded_image = create_figure(date) return html.Div([ html.Img(src='data:image/png;base64,{}'.format(encoded_image.decode()), style={"text-align": "center"}) ])
if __name__ == '__main__': app.run_server(debug=True)Plotly + Dash 框架
@app.callback( Output('output-container-date-picker-single', 'children'), [Input('my-date-picker-single', 'date')])def update_output(date): print("date", date) if date is not None: if date not in date_list: return html.Div([ "数据不存在" ]) fig = create_figure(date) return html.Div([ dcc.Graph(figure=fig) ])
if __name__ == '__main__': app.run_server(debug=True) # 启动应用程序8. 结语
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