> For the complete documentation index, see [llms.txt](https://docs.trymito.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.trymito.io/how-to-1/pass-a-dataframe-into-mito.md).

# Pass a dataframe into Mito

Query a database, or scrape a table from a website and import the dataframe into Mito. Import any Pandas dataframe into Mito.

#### Import Python Packages

To import a dataframe into Mito, we need the Mito and pandas packages. Both are distributed through the Mito installer. If you have not yet installed Mito, follow the instructions [here](/getting-started/installing-mito.md). 

```python
# Import Python packages
import mitosheet 
import pandas as pd
```

#### Create the Pandas Dataframes 

Using Pandas, you can create dataframes by [reading csv files](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html), [Excel files](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html), or even [querying an SQL database](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_sql_query.html). 

For the purposes of this tutorial, we will create two sample dataframes. 

```python
# Create some simple data to display 
train_stations = pd.DataFrame({'Zip': [21001, 97321, 49224, 87102, 24910, 22301], 'City': ['Aberdeen', 'Albany', 'Albion', 'Albuquerque', 'Alderson', 'Alexandria'], 'State': ['MD', 'OR', 'MI', 'NM', 'WV', 'VA'], 'Ticket_Office': ['N', 'Y', 'N', 'Y', 'N', 'Y']}) 
demographics = pd.DataFrame({'Zip': [21001, 97321, 49224, 87102, 24910, 22301], 'Median_Income': [53979.0, 112924.0, 37556.0, 28388.0, 30914.0, 54087.0], 'Mean_Income': [66169.0, 147076.0, 50371.0, 39529.0, 40028.0, 64068.0], 'Pop': [18974.0, 11162.0, 14900.0, 22204.0, 5383.0, 19504.0]})
```

#### Pass the dataframes into Mito

To import the dataframe into Mito, just provide it as an argument to the mitosheet.sheet() function call. 

```python
# Render the Mitosheet with the data
mitosheet.sheet(train_stations, demographics)
```


---

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