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Dataframe

gradio.Dataframe(ยทยทยท)

Description

Accepts or displays 2D input through a spreadsheet-like component for dataframes.

Behavior

As input: passes the uploaded spreadsheet data as a pandas.DataFrame, numpy.array, List[List], or List depending on `type`

As output: expects a pandas.DataFrame, numpy.array, List[List], List, a Dict with keys `data` (and optionally `headers`), or str path to a csv, which is rendered in the spreadsheet.

Initialization

Parameter Description
value

list[list[Any]] | Callable | None

default: None

Default value as a 2-dimensional list of values. If callable, the function will be called whenever the app loads to set the initial value of the component.

headers

list[str] | None

default: None

List of str header names. If None, no headers are shown.

row_count

int | tuple[int, str]

default: (1, 'dynamic')

Limit number of rows for input and decide whether user can create new rows. The first element of the tuple is an `int`, the row count; the second should be 'fixed' or 'dynamic', the new row behaviour. If an `int` is passed the rows default to 'dynamic'

col_count

int | tuple[int, str] | None

default: None

Limit number of columns for input and decide whether user can create new columns. The first element of the tuple is an `int`, the number of columns; the second should be 'fixed' or 'dynamic', the new column behaviour. If an `int` is passed the columns default to 'dynamic'

datatype

str | list[str]

default: "str"

Datatype of values in sheet. Can be provided per column as a list of strings, or for the entire sheet as a single string. Valid datatypes are "str", "number", "bool", "date", and "markdown".

type

Literal[('pandas', 'numpy', 'array')]

default: "pandas"

Type of value to be returned by component. "pandas" for pandas dataframe, "numpy" for numpy array, or "array" for a Python array.

max_rows

int | None

default: 20

Maximum number of rows to display at once. Set to None for infinite.

max_cols

int | None

default: None

Maximum number of columns to display at once. Set to None for infinite.

overflow_row_behaviour

Literal[('paginate', 'show_ends')]

default: "paginate"

If set to "paginate", will create pages for overflow rows. If set to "show_ends", will show initial and final rows and truncate middle rows.

latex_delimiters

list[dict[str, str | bool]] | None

default: None

A list of dicts of the form {"left": open delimiter (str), "right": close delimiter (str), "display": whether to display in newline (bool)} that will be used to render LaTeX expressions. If not provided, `latex_delimiters` is set to `[{ "left": "$", "right": "$", "display": False }]`, so only expressions enclosed in $ delimiters will be rendered as LaTeX, and in the same line. Pass in an empty list to disable LaTeX rendering. For more information, see the [KaTeX documentation](https://katex.org/docs/autorender.html). Only applies to columns whose datatype is "markdown".

label

str | None

default: None

component name in interface.

every

float | None

default: None

If `value` is a callable, run the function 'every' number of seconds while the client connection is open. Has no effect otherwise. Queue must be enabled. The event can be accessed (e.g. to cancel it) via this component's .load_event attribute.

show_label

bool | None

default: None

if True, will display label.

height

int | float | None

default: None

The maximum height of the file component, in pixels. If more files are uploaded than can fit in the height, a scrollbar will appear.

scale

int | None

default: None

relative width compared to adjacent Components in a Row. For example, if Component A has scale=2, and Component B has scale=1, A will be twice as wide as B. Should be an integer.

min_width

int

default: 160

minimum pixel width, will wrap if not sufficient screen space to satisfy this value. If a certain scale value results in this Component being narrower than min_width, the min_width parameter will be respected first.

interactive

bool | None

default: None

if True, will allow users to edit the dataframe; if False, can only be used to display data. If not provided, this is inferred based on whether the component is used as an input or output.

visible

bool

default: True

If False, component will be hidden.

elem_id

str | None

default: None

An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.

elem_classes

list[str] | str | None

default: None

An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.

wrap

bool

default: False

if True text in table cells will wrap when appropriate, if False the table will scroll horizontally. Defaults to False.

Shortcuts

Class Interface String Shortcut Initialization

gradio.Dataframe

"dataframe"

Uses default values

gradio.Numpy

"numpy"

Uses type="numpy"

gradio.Matrix

"matrix"

Uses type="array"

gradio.List

"list"

Uses type="array", col_count=1

Demos

import gradio as gr


def filter_records(records, gender):
    return records[records["gender"] == gender]


demo = gr.Interface(
    filter_records,
    [
        gr.Dataframe(
            headers=["name", "age", "gender"],
            datatype=["str", "number", "str"],
            row_count=5,
            col_count=(3, "fixed"),
        ),
        gr.Dropdown(["M", "F", "O"]),
    ],
    "dataframe",
    description="Enter gender as 'M', 'F', or 'O' for other.",
)

if __name__ == "__main__":
    demo.launch()

Event Listeners

Description

Event listeners allow you to capture and respond to user interactions with the UI components you've defined in a Gradio Blocks app. When a user interacts with an element, such as changing a slider value or uploading an image, a function is called.

Supported Event Listeners

The Dataframe component supports the following event listeners. Each event listener takes the same parameters, which are listed in the Event Arguments table below.

Listener Description

gradio.Dataframe.change(fn, ยทยทยท)

This listener is triggered when the component's value changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input.

gradio.Dataframe.input(fn, ยทยทยท)

This listener is triggered when the user changes the value of the component.

gradio.Dataframe.select(fn, ยทยทยท)

Event listener for when the user selects cell within Dataframe. Uses event data gradio.SelectData to carry `value` referring to value of selected cell, and `index` tuple to refer to index row and column. See EventData documentation on how to use this event data.

Event Arguments

Parameter Description
fn

Callable | None | Literal['decorator']

default: "decorator"

the function to call when this event is triggered. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component.

inputs

Component | Sequence[Component] | set[Component] | None

default: None

List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list.

outputs

Component | Sequence[Component] | None

default: None

List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list.

api_name

str | None | Literal[False]

default: None

Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name.

status_tracker

None

default: None

Deprecated and has no effect.

scroll_to_output

bool

default: False

If True, will scroll to output component on completion

show_progress

Literal[('full', 'minimal', 'hidden')] | None

default: None

If True, will show progress animation while pending

queue

bool | None

default: None

If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app.

batch

bool

default: False

If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component.

max_batch_size

int

default: 4

Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True)

preprocess

bool

default: True

If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component).

postprocess

bool

default: True

If False, will not run postprocessing of component data before returning 'fn' output to the browser.

cancels

dict[str, Any] | list[dict[str, Any]] | None

default: None

A list of other events to cancel when this listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish.

every

float | None

default: None

Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled.