pyecharts實現數據可視化
1.概述
pyecharts 是百度開源的,適用於數據可視化的工具,配置靈活,展示圖表相對美觀,順滑。
2.安裝
python3環境下的安裝:
pip3 install pyecharts
3.數據可視化代碼
3.1 柱狀圖
from pyecharts import options as opts from pyecharts.charts import Bar from pyecharts.faker import Faker c = ( Bar() .add_xaxis(Faker.choose()) .add_yaxis("商傢A", Faker.values(), stack="stack1") .add_yaxis("商傢B", Faker.values(), stack="stack1") .set_series_opts(label_opts=opts.LabelOpts(is_show=False)) .set_global_opts(title_opts=opts.TitleOpts(title="Bar-堆疊數據(全部)")) .render("bar_stack0.html") )
執行上述代碼,會在相對目錄生成mycharts.html
文件,通過頁面打開。
3.2 折線圖
import pyecharts.options as opts from pyecharts.charts import Line """ Gallery 使用 pyecharts 1.1.0 參考地址: https://echarts.apache.org/examples/editor.html?c=line-smooth 目前無法實現的功能: 暫無 """ x_data = ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"] y_data = [820, 932, 901, 934, 1290, 1330, 1320] ( Line() .set_global_opts( tooltip_opts=opts.TooltipOpts(is_show=False), xaxis_opts=opts.AxisOpts(type_="category"), yaxis_opts=opts.AxisOpts( type_="value", axistick_opts=opts.AxisTickOpts(is_show=True), splitline_opts=opts.SplitLineOpts(is_show=True), ), ) .add_xaxis(xaxis_data=x_data) .add_yaxis( series_name="", y_axis=y_data, symbol="emptyCircle", is_symbol_show=True, is_smooth=True, label_opts=opts.LabelOpts(is_show=False), ) .render("smoothed_line_chart.html") )
3.3 餅圖
from pyecharts import options as opts from pyecharts.charts import Pie from pyecharts.faker import Faker c = ( Pie() .add( "", [list(z) for z in zip(Faker.choose(), Faker.values())], radius=["40%", "75%"], ) .set_global_opts( title_opts=opts.TitleOpts(title="Pie-Radius"), legend_opts=opts.LegendOpts(orient="vertical", pos_top="15%", pos_left="2%"), ) .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}")) .render("pie_radius.html") )
到此這篇關於pyecharts實現數據可視化的文章就介紹到這瞭,更多相關pyecharts數據可視化內容請搜索WalkonNet以前的文章或繼續瀏覽下面的相關文章希望大傢以後多多支持WalkonNet!
推薦閱讀:
- Python echarts實現數據可視化實例詳解
- Python繪制散點圖之可視化神器pyecharts
- Python pyecharts Line折線圖的具體實現
- Python繪制折線圖可視化神器pyecharts案例
- Python可視化神器pyecharts繪制地理圖表