# Various types of charts

All chart types provided by PowerPoint are supported.&#x20;

Here are a few examples:&#x20;

* [#line-chart](#line-chart "mention")
* [#bar-chart](#bar-chart "mention")
* [#stacked-bar-chart](#stacked-bar-chart "mention")
* [#stacked-area-chart](#stacked-area-chart "mention")
* [#bar-line-combo-chart](#bar-line-combo-chart "mention")
* [#scatter-chart](#scatter-chart "mention")

These can be customized using the standard `data` and `settings` parameters in your payload.

Reference: [chart](/json-template-syntax/shapes/chart.md)

### Line chart

Download: [input.zip](https://drive.google.com/uc?export=download\&id=1kteeNIRCLhVbHEyhogaeSBCOqsG_3mcu) | [output.pptx](https://drive.google.com/uc?export=download\&id=1Y1eHtkroJU2BPQeG0j4-Q3u1H5-xV2FD)

{% columns %}
{% column width="41.66666666666667%" %}

<figure><img src="/files/7I4FE7sfW1ASRb1JCisC" alt=""><figcaption></figcaption></figure>

***

<figure><img src="/files/tgTLdWxlyPo5YDQ8Sw2F" alt=""><figcaption></figcaption></figure>
{% endcolumn %}

{% column width="58.33333333333333%" %}
{% code lineNumbers="true" %}

```json
{
  "presentation": {
    "template": "template.pptx",
    "slides": [
      {
        "slide_index": 0,
        "shapes": [
          {
            "name": "Chart 1",
            "title": "Quarterly Business Performance (2025)",
            "data": [
              [
                "Revenue",
                "Expenses",
                "Profit"
              ],
              [
                "Q1",
                "Q2",
                "Q3",
                "Q4"
              ],
              [
                5.2,
                3.1,
                4.6
              ],
              [
                2.8,
                2.5,
                3.2
              ],
              [
                2.4,
                0.6,
                1.4
              ],
              [
                1.3,
                4.0,
                2.4
              ]
            ]
          }
        ]
      }
    ]
  }
}

```

{% endcode %}
{% endcolumn %}
{% endcolumns %}

### Bar chart

Download: [input.zip](https://drive.google.com/uc?export=download\&id=1lk_eGi3UEAZWkL88PvGLx-saUFY1edt4) | [output.pptx](https://drive.google.com/uc?export=download\&id=1RgJyUc6fQIA0i2W_Sz6hz2wBUNIQO_WS)

{% columns %}
{% column width="41.66666666666667%" %}

<figure><img src="/files/eYKminMWSgiHPiKGG0bx" alt=""><figcaption></figcaption></figure>

***

<figure><img src="/files/9OLZwwvgpmTqov744XAZ" alt=""><figcaption></figcaption></figure>
{% endcolumn %}

{% column width="58.33333333333333%" %}
{% code lineNumbers="true" %}

```json
{
  "presentation": {
    "template": "template.pptx",
    "slides": [
      {
        "slide_index": 0,
        "shapes": [
          {
            "name": "Chart 1",
            "title": "Average Annual Precipitations",
            "data": [
              [
                "North",
                "South",
                "East",
                "West"
              ],
              [
                "January",
                "February",
                "March",
                "April"
              ],
              [
                11,
                15,
                4,
                7
              ],
              [
                15,
                35,
                23,
                18
              ],
              [
                40,
                50,
                65,
                44
              ],
              [
                60,
                73,
                52,
                68
              ]
            ]
          }
        ]
      }
    ]
  }
}
```

{% endcode %}
{% endcolumn %}
{% endcolumns %}

### Stacked Bar chart

Download: [input.zip](https://drive.google.com/uc?export=download\&id=1SA0jxYaBBqKb0GCfCTy2X9XYxklPc6D5) | [output.pptx](https://drive.google.com/uc?export=download\&id=1hxA14ZozN79ktO-19WUsvWfkOjgp2dIA)

{% columns %}
{% column width="41.66666666666667%" %}

<figure><img src="/files/nTh35mdsiKOYvvRec0wz" alt=""><figcaption></figcaption></figure>

***

<figure><img src="/files/4vqJx9VNcVMWkK0yPkfy" alt=""><figcaption></figcaption></figure>
{% endcolumn %}

{% column width="58.33333333333333%" %}
{% code lineNumbers="true" %}

```json
{
  "presentation": {
    "template": "template.pptx",
    "slides": [
      {
        "slide_index": 0,
        "shapes": [
          {
            "name": "Chart 1",
            "title": "Monthly Revenue Breakdown (2025)",
            "data": [
              [
                "Online Sales",
                "In-Store Sales"
              ],
              [
                "January",
                "February",
                "March",
                "April",
                "May",
                "June"
              ],
              [
                12000,
                9500
              ],
              [
                18000,
                11000
              ],
              [
                22000,
                13000
              ],
              [
                19500,
                14000
              ],
              [
                25000,
                12500
              ],
              [
                17000,
                9000
              ]
            ]
          }
        ]
      }
    ]
  }
}

```

{% endcode %}
{% endcolumn %}
{% endcolumns %}

### Stacked Area chart

Download: [input.zip](https://drive.google.com/uc?export=download\&id=1YXddibN0CubzzTtQZJ7CyRldyY3t6L-o) | [output.pptx](https://drive.google.com/uc?export=download\&id=172hHYimihH-DAIPwHbajOM6AKxEI6FDc)

{% columns %}
{% column width="41.66666666666667%" %}

<figure><img src="/files/OfmTJXNKqAJ2CfFi3Dnh" alt=""><figcaption></figcaption></figure>

***

<figure><img src="/files/ZncLHQjPYfFObbBmh4X4" alt=""><figcaption></figcaption></figure>
{% endcolumn %}

{% column width="58.33333333333333%" %}
{% code lineNumbers="true" %}

```json
{
  "presentation": {
    "template": "template.pptx",
    "slides": [
      {
        "slide_index": 0,
        "shapes": [
          {
            "name": "Chart 1",
            "title": "Monthly Revenue Breakdown (2025)",
            "data": [
              [
                "Online Sales",
                "In-Store Sales"
              ],
              [
                "January",
                "February",
                "March",
                "April",
                "May",
                "June"
              ],
              [
                12000,
                9500
              ],
              [
                18000,
                11000
              ],
              [
                22000,
                13000
              ],
              [
                19500,
                14000
              ],
              [
                25000,
                12500
              ],
              [
                17000,
                9000
              ]
            ]
          }
        ]
      }
    ]
  }
}

```

{% endcode %}
{% endcolumn %}
{% endcolumns %}

### Bar/Line Combo chart

Download: [input.zip](https://drive.google.com/uc?export=download\&id=1HguMn9OrUH2Gw_VKZyxoP1ptotQ_qX8L) | [output.pptx](https://drive.google.com/uc?export=download\&id=1mZWNA8Y4xeuKG_VW5dZ6H1AdPxM5ru3K)

{% columns %}
{% column width="41.66666666666667%" %}

<figure><img src="/files/bOwZGLcEJm2Oi6hPWKWm" alt=""><figcaption></figcaption></figure>

***

<figure><img src="/files/C8XkxB6PdyEbJ0rEAGPR" alt=""><figcaption></figcaption></figure>
{% endcolumn %}

{% column width="58.33333333333333%" %}
{% code lineNumbers="true" %}

```json
{
  "presentation": {
    "template": "template.pptx",
    "slides": [
      {
        "slide_index": 0,
        "shapes": [
          {
            "name": "Chart 1",
            "title": "Quarterly Sales and Profit Margin",
            "data": [
              [
                "North Region",
                "South Region",
                "Profit Margin"
              ],
              [
                "Q1",
                "Q2",
                "Q3",
                "Q4"
              ],
              [
                32000,
                27000,
                35000
              ],
              [
                28000,
                30000,
                33000
              ],
              [
                38000,
                36000,
                41000
              ],
              [
                42000,
                39000,
                45000
              ]
            ]
          }
        ]
      }
    ]
  }
}
```

{% endcode %}
{% endcolumn %}
{% endcolumns %}

### Scatter chart

Download: [input.zip](https://drive.google.com/uc?export=download\&id=1lrQgT1_9WT9aDoT7XT-2J41xgyH3kP9K) | [output.pptx](https://drive.google.com/uc?export=download\&id=1DoIaMlZ0g0llCyA11kCKEdbSU9e2gWRq)

{% columns %}
{% column width="41.66666666666667%" %}

<figure><img src="/files/xVtWNvWADBCQpiIrunpB" alt=""><figcaption></figcaption></figure>

***

<figure><img src="/files/Ak6cdM0rAJPSYwXPnSdt" alt=""><figcaption></figcaption></figure>
{% endcolumn %}

{% column width="58.33333333333333%" %}
{% code lineNumbers="true" %}

```json
{
  "presentation": {
    "template": "template.pptx",
    "slides": [
      {
        "slide_index": 0,
        "shapes": [
          {
            "name": "Plot",
            "data": [
              [
                "a",
                "b",
                "c"
              ],
              [
                3.8,
                3.2,
                7.6,
                9.3
              ],
              [
                7.2,
                5.5,
                6.3,
                4.1
              ],
              [
                6.2,
                4.5,
                5.3,
                3.1
              ],
              [
                1.2,
                3.5,
                9.3,
                1.1
              ]
            ],
            "additional_data": [
              {
                "cell_target": "A2",
                "data": [
                  [
                    "A"
                  ],
                  [
                    "B"
                  ],
                  [
                    "C"
                  ],
                  [
                    "D"
                  ]
                ]
              }
            ]
          }
        ]
      }
    ]
  }
}
```

{% endcode %}
{% endcolumn %}
{% endcolumns %}


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