colors = dict(zip(state_list, sns.color_palette("GnBu_d", len(state_list)).as_hex())) trace_list = [] for state in state_list: trace = go.Scatter( y=df_state[df_state['RegionName']==state]['ZHVI_BottomTier'].tolist(), x=df_state[df_state['RegionName']==state]['Date'...
mode="lines+markers",name="ZHVI_1bedroom",marker=dict(color='rgb(102,255,255)'),text=df_groupby_datebr['ZHVI_1bedroom'])trace2=go.Scatter(x=df_groupby_datebr.index.values,y=df_groupby_datebr.ZHVI_2bedroom,mode="lines+markers",name="ZHVI_2bedroom",marker=dict(color='rgb(102...
name="ZHVI_1bedroom",marker=dict(color='rgb(102,255,255)'),text=df_groupby_datebr['ZHVI_1bedroom'])trace2=go.Bar(x=df_groupby_datebr.index.values,y=df_groupby_datebr.ZHVI_2bedroom,name="ZHVI_2bedroom",marker=dict(color='rgb(102,178,255)'),text=df_groupby_datebr['ZHVI_2...
5、Plotly时序线图 下面的代码绘制时序线图: #Time Series Line Chart state_list = df_state.groupby('RegionName')[['ZHVI_BottomTier']].mean().sort_values( by='ZHVI_BottomTier', ascending=False)[:5].index.values.tolist() colors = dict(zip(state_list, sns.color_palette("GnBu_d", len...
100000], range_y=[25, 90], # color_continuous_scale=px.colors.sequential.Emrld ...
color[df .set_index("concerns", drop=True) .iloc[::-1] ["concerns per 1,000"]<10] = gray_palette[4] 然后我们直接从 DataFrame 创建绘图。 (df .set_index("concerns", drop=True) .iloc[::-1] .plot .barh() .update_traces(marker=dict(color=color.tolist())) ...
(df.set_index("concerns",drop=True).iloc[::-1].plot.barh().update_traces(marker=dict(color=color.tolist())).update_layout(template="plotly_white",title=dict(text="Top 10 design concerns concerns per 1,000",font_size=30,font_color=gray_palette[4]),margin=...
1)利用ColorBrewer Palette Names定义颜色,形状 大小 p <- plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, color = ~Species #颜色分类 ,symbol = ~Species , symbols = c('circle','x','o')#符号分类及对应的表示符号
图片的标题 plt.title(string,color=,size=,loc=) X轴的标签 plt.xlabel() Y轴的标签 plt.ylabel() 确定X轴范围 plt.xlim() 确定Y轴范围 plt.ylim() 确定X轴的标签刻度 plt.xticks() 确定Y轴的标签刻度 plt.yticks() plt.plot(x,y,c='red',lw=3,ls='--',marker='o',markersize=10,markeredg...
population散点图-漫步时光fig = px.scatter(data_frame=data,x="Log GDP per capita",y="Life Ladder",animation_frame="Year",animation_group="Country name",size="Gapminder Population",color="Continent",hover_name="Country name",facet_col="Continent",size_max=45,category_orders={'Year':list(...