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If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
若遇到不熟悉的占位符或需要查看已连接的工具,请参考 CONNECTORS.md。
/create-viz <data source> [chart type] [additional instructions]/create-viz <数据源> [图表类型] [额外说明]| Data Relationship | Recommended Chart |
|---|---|
| Trend over time | Line chart |
| Comparison across categories | Bar chart (horizontal if many categories) |
| Part-to-whole composition | Stacked bar or area chart (avoid pie charts unless <6 categories) |
| Distribution of values | Histogram or box plot |
| Correlation between two variables | Scatter plot |
| Two-variable comparison over time | Dual-axis line or grouped bar |
| Geographic data | Choropleth map |
| Ranking | Horizontal bar chart |
| Flow or process | Sankey diagram |
| Matrix of relationships | Heatmap |
| 数据关系 | 推荐图表 |
|---|---|
| 随时间变化的趋势 | 折线图 |
| 跨类别对比 | 柱状图(类别较多时使用横向柱状图) |
| 整体与部分的构成 | 堆叠柱状图或面积图(除非类别少于6个,否则避免使用饼图) |
| 数值分布 | 直方图或箱线图 |
| 两个变量的相关性 | 散点图 |
| 双变量随时间的对比 | 双轴折线图或分组柱状图 |
| 地理数据 | 分级统计图 |
| 排名排序 | 横向柱状图 |
| 流程或流向 | 桑基图 |
| 关系矩阵 | 热力图 |
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pdimport matplotlib.pyplot as plt
import seaborn as sns
import pandas as pdundefinedundefined/create-viz Show monthly revenue for the last 12 months as a line chart with the trend highlighted/create-viz Here's our NPS data by product: [pastes data]. Create a horizontal bar chart ranking products by score./create-viz Query the orders table and create a heatmap of order volume by day-of-week and hour/create-viz 展示过去12个月的月度营收,用折线图呈现并突出趋势/create-viz 这是我们按产品划分的NPS数据:[粘贴数据]。创建横向柱状图,按得分对产品进行排名。/create-viz 查询订单表,创建按星期几和小时分布的订单量热力图