# Requirements of charts
### Measures and dimensions required for each chart
The following are the essential requirements for building effective and insightful charts. Get the minimum number of measures and dimensions needed for each chart type.
| Chart | Min. measures | Min. dimensions |
|---|
| KPI | 1 | 0 |
| Pie chart | 1 | 1 |
| Bar chart | 1 | 1 |
| Line chart | 1 | 1 |
| Scatter plot | 2 | 1 |
| Combo chart | 1 | 1 |
| Table | n | n |
| Detail table | n | n |
| Pivot table | n | n |
| Histogram | 1 | 0 |
| Heatmap | 1 | 2 |
| Treemap | 1 | 1 |
| Sankey chart | 1 | 2 |
| Bubble chart | 1 | 1 |
| Boundary map | 0 | 1 (geo dimension) |
| Location map | 0 | 2 (latitude & longitude) |
| Waterfall chart | 1 | 1 |
| KPI target chart | 1 | 0 |
| Growth chart | 1 | 1 |
| Funnel chart | 1 | 1 |
| Bar conversion | n | 0 |
| Confidence range | 3 | 1 |
| YoY chart | 1 | 1 (date) |
| Cohort chart | 1 | 2 |
### Data point limits for each chart
In this section, we'll outline the default number of data points allowed for various chart types. Understanding these limits is crucial for creating effective and visually appealing charts.
| Type of chart(s) | Default limit of data points |
| --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :--------------------------: |
| - Line chart
- Area chart
- Growth/Trend chart
- Combined bar chart
- Heatmap
- Confidence range chart
- Scatter chart
| 10,000 |
| Bubble chart | 5000 |
| Treemap, Bar chart | 1000 |
| Location map, Boundary map | 1000 |
| Pivot table, Cohort chart | 500 |
| Waterfall chart | 100 |
| Pie/Donut chart, Funnel chart, Tables | 50 |
### **Optimizing your chart data**
Understanding the default data point limits for different chart types is essential for effective data visualization. However, there may be instances where you need to work with larger datasets. In such cases, consider the following options for better data representation:
1. **Alternative chart types**: Explore alternative chart types that are better suited for larger datasets. For example, if you're dealing with extensive data, a scatter plot or a bar chart might be more appropriate than a pie chart.
2. **Data optimization**: Before creating your chart, consider optimizing your dataset. This can involve summarizing or aggregating your data to reduce the number of data points while retaining key insights.