# Graph Creation

### Opening a new graph

To begin creating a graph, click the `Graph` button in `Home` tab of the Mito toolbar. This will open up a blank graph that you can then begin to configure.

### Setting up the graph

`Data Source`: The sheet that contains the data that you want to graph.

`Chart Type`: The type of graph that you want to create. Mito supports:

* [Scatter plots](https://plotly.com/python/line-and-scatter/)
* [Line charts](https://plotly.com/python/line-charts/)
* [Bar charts](https://plotly.com/python/bar-charts/)
* [Histograms](https://plotly.com/python/histograms/)
* [Box plots](https://plotly.com/python/box-plots/)
* [Violin plots](https://plotly.com/python/violin/)
* [Strip plots](https://plotly.com/python/strip-charts/)
* [Density heatmaps](https://plotly.com/python/2D-Histogram/)
* [Density Countour maps](https://plotly.com/python/2d-histogram-contour/)
* [ECDF (Emprical Cumulative Distribution Function) graphs](https://plotly.com/python/ecdf-plots/)

`X Axis`: The data to graph along the x axis.

* You can select multiple series either along the x or y axis (not both) as long as the series have similar dtypes.

`Y Axis`: The data to graph along the y axis.

* You can select multiple series either along the x or y axis (not both) as long as the series have similar dtypes.

`Color by Column`: An additional column to further breakdown the graphed data using the color attribute.

* For best results, select a column with few unique values.
* This option is selectable for all graphs expect the `Density heatmap`.

`Filter to safe size`: By default, Mito only graphs the first 1000 rows of data to ensure that the browser tab doesn't crash while attempting to load too much data into the graph. Turning off filter to save size graphs the entire dataframe and may slow down or crash your browser tab.

<figure><img src="/files/oifXVZU0vOBnPsKOMeT2" alt=""><figcaption><p>Setting up a graph in Mito</p></figcaption></figure>

### Graph Specific Configurations

Configure specific graph parameters: for Histograms, set the number of bins, for line plots, define how the line is build, etc.

### Facet Plot

Configure the graph by splitting into multiple subplots (or facet plots) based on a column in your dataframe.


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