pyechats 人口分析可视化

Author: budaLi

人口分析/Population of India (2020 and historical).xlsx

@@ -0,0 +1,110 @@
+# @Time    : 2020/5/29 9:20
+# @Author  : Libuda
+# @FileName: analyze.py
+# @Software: PyCharm
+import numpy as np
+import pandas as pd
+import pyecharts.options as opts
+from pyecharts.charts import Line, Bar, Page, Pie
+from pyecharts.commons.utils import JsCode
+
+# 人口数量excel文件保存路径
+POPULATION_EXCEL_PATH = 'Population of India (2020 and historical).xlsx'
+
+# 读取标准数据
+DF_STANDARD = pd.read_excel(POPULATION_EXCEL_PATH)
+print(DF_STANDARD)
+# 自定义pyecharts图形背景颜色js
+background_color_js = (
+    "new echarts.graphic.LinearGradient(0, 0, 0, 1, "
+    "[{offset: 0, color: '#c86589'}, {offset: 1, color: '#06a7ff'}], false)"
+)
+# 自定义pyecharts图像区域颜色js
+area_color_js = (
+    "new echarts.graphic.LinearGradient(0, 0, 0, 1, "
+    "[{offset: 0, color: '#eb64fb'}, {offset: 1, color: '#3fbbff0d'}], false)"
+)
+
+
+def analysis_total():
+    """
+    分析总人口
+    """
+    # 1、分析总人口，画人口曲线图
+    # 1.1 处理数据
+    x_data = DF_STANDARD['Year'][::-1]
+    # 将人口单位转换为万
+    y_data = DF_STANDARD['Population'].map(lambda x: "%.2f" % (x / 10000))[::-1]
+    # y_data = DF_STANDARD['Population'][::-1]
+    # 1.2 自定义曲线图
+    line = (
+        Line(init_opts=opts.InitOpts(bg_color=JsCode(background_color_js)))
+            .add_xaxis(xaxis_data=x_data)
+            .add_yaxis(
+            series_name="总人口",
+            y_axis=y_data,
+            is_smooth=True,
+            is_symbol_show=True,
+            symbol="circle",
+            symbol_size=5,
+            linestyle_opts=opts.LineStyleOpts(color="#fff"),
+            label_opts=opts.LabelOpts(is_show=False, position="top", color="white"),
+            itemstyle_opts=opts.ItemStyleOpts(
+                color="red", border_color="#fff", border_width=1
+            ),
+            tooltip_opts=opts.TooltipOpts(is_show=False),
+            areastyle_opts=opts.AreaStyleOpts(color=JsCode(area_color_js), opacity=1),
+        )
+            .set_global_opts(
+            title_opts=opts.TitleOpts(
+                title="印度人口变化(万人)",
+                pos_bottom="5%",
+                pos_left="center",
+                title_textstyle_opts=opts.TextStyleOpts(color="#fff", font_size=16),
+            ),
+            # x轴相关的选项设置
+            xaxis_opts=opts.AxisOpts(
+                type_="category",
+                boundary_gap=False,
+                axislabel_opts=opts.LabelOpts(margin=30, color="#ffffff63"),
+                axisline_opts=opts.AxisLineOpts(is_show=False),
+                axistick_opts=opts.AxisTickOpts(
+                    is_show=True,
+                    length=25,
+                    linestyle_opts=opts.LineStyleOpts(color="#ffffff1f"),
+                ),
+                splitline_opts=opts.SplitLineOpts(
+                    is_show=False, linestyle_opts=opts.LineStyleOpts(color="#ffffff1f")
+                ),
+            ),
+            # y轴相关选项设置
+            yaxis_opts=opts.AxisOpts(
+                type_="value",
+                position="left",
+                axislabel_opts=opts.LabelOpts(margin=20, color="#ffffff63"),
+                axisline_opts=opts.AxisLineOpts(
+                    linestyle_opts=opts.LineStyleOpts(width=0, color="#ffffff1f")
+                ),
+                axistick_opts=opts.AxisTickOpts(
+                    is_show=True,
+                    length=15,
+                    linestyle_opts=opts.LineStyleOpts(color="#ffffff1f"),
+                ),
+                splitline_opts=opts.SplitLineOpts(
+                    is_show=False, linestyle_opts=opts.LineStyleOpts(color="#ffffff1f")
+                ),
+            ),
+            # 图例配置项相关设置
+            legend_opts=opts.LegendOpts(is_show=False),
+        )
+    )
+    # 3、渲染图像，将多个图像显示在一个html中
+    # DraggablePageLayout表示可拖拽
+    page = Page(layout=Page.SimplePageLayout)
+    page.add(line)
+    # page.add(bar)
+    page.render('population_total.html')
+
+
+if __name__ == '__main__':
+    analysis_total()