title: Python 3D Bubble Charts | plotly

import plotly.express as px

title: 3D Line Plots in Python | plotly

import plotly.express as px

v4upgrade: true

[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on "tidy" data](/python/px-arguments/).

v4upgrade: true

import plotly.express as px

fig.show()

import plotly.express as px

Axis tick marks are disabled by default for the default `plotly` theme, but they can easily be turned on by setting the `ticks` axis property to `"inside"` (to place ticks inside plotting area) or `"outside"` (to place ticks outside the plotting area).

import plotly.express as px

The axis tick mark labels can be disabled by setting the `showticklabels` axis property to `False`.

import plotly.express as px

The approximate number of ticks displayed for an axis can be specified using the `nticks` axis property.

import plotly.express as px

The `tick0` and `dtick` axis properties can be used to control to placement of axis ticks as follows: If specified, a tick will fall exactly on the location of `tick0` and additional ticks will be added in both directions at intervals of `dtick`.

import plotly.express as px

It is possible to configure an axis to display ticks at a set of predefined locations by setting the `tickvals` property to an array of positions.

import plotly.express as px

The appearance of these tick marks can be customized by setting their length (`ticklen`), width (`tickwidth`), and color (`tickcolor`).

import plotly.express as px

import plotly.express as px

The orientation of the axis tick mark labels is configured using the `tickangle` axis property. The value of `tickangle` is the angle of rotation, in the clockwise direction, of the labels from vertical in units of degrees. The font family, size, and color for the tick labels are stored under the `tickfont` axis property.

import plotly.express as px

The `showline` axis property controls the visibility of the axis line, and the `linecolor` and `linewidth` axis properties control the color and width of the axis line.

import plotly.express as px

Axis lines can be mirrored to the opposite side of the plotting area by setting the `mirror` axis property to `True`.

import plotly.express as px

The width and color of axis grid lines are controlled by the `gridwidth` and `gridcolor` axis properties.

import plotly.express as px

The visible x and y axis range can be configured manually by setting the `range` axis property to a list of two values, the lower and upper boundary.

import plotly.express as px

You can tell plotly's automatic axis range calculation logic to reverse the direction of an axis by setting the `autorange` axis property to `"reversed"`.

import plotly.express as px

The direction of an axis can be reversed when manually setting the range extents by specifying a list containing the upper bound followed by the lower bound (rather that the lower followed by the upper) as the `range` axis property.

import plotly.express as px

If `rangemode` is `"normal"` (the default), the range is computed based on the min and max values of the input data. If `"tozero"`, the the range will always include zero. If `"nonnegative"`, the range will not extend below zero, regardless of the input data.

import plotly.express as px

v4upgrade: true

[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on "tidy" data](/python/px-arguments/).

data_canada

The bar plot can be customized using keyword arguments.

A [box plot](https://en.wikipedia.org/wiki/Box_plot) is a statistical representation of numerical data through their quartiles. The ends of the box represent the lower and upper quartiles, while the median (second quartile) is marked by a line inside the box. For other statistical representations of numerical data, see [other statistical charts](https://plot.ly/python/statistical-charts/).

[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on "tidy" data](/python/px-arguments/).

A [bubble chart](https://en.wikipedia.org/wiki/Bubble_chart) is a scatter plot in which a third dimension of the data is shown through the size of markers. For other types of scatter plot, see the [line and scatter page](https://plot.ly/python/line-and-scatter/).

import plotly.express as px

v4upgrade: true

[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on "tidy" data](/python/px-arguments/). With ``px.scatter_geo``, each line of the dataframe is represented as a marker point. The column set as the `size` argument gives the size of markers.

v4upgrade: true

A collection of predefined sequential colorscales is provided in the `plotly.express.colors.sequential` module.

import plotly.express as px

name: Creating and Updating Figures

page_type: example_index

permalink: python/creating-and-updating-figures/

- python/user-guide/

- python/user-g/

thumbnail: thumbnail/creating-and-updating-figures.png

fig.show()

import plotly.express as px

fig.show()

import plotly.express as px

fig.show()

import pandas as pd

As its first argument, the `for_each_trace` method accepts a function that accepts and updates one trace at a time. Like `update_traces`, `for_each_trace` also accepts `selector`, `row`, and `col` arguments to control which traces should be considered.

import pandas as pd

import pandas as pd

All of the figure update operations described above are methods that return a reference to the figure being modified. This makes it possible the chain multiple figure modification operations together into a single expression.

import plotly.express as px

v4upgrade: true

[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on "tidy" data](/python/px-arguments/). For functions representing 2D data points such as [`px.scatter`](https://plot.ly/python/line-and-scatter/), [`px.line`](https://plot.ly/python/line-charts/), [`px.bar`](https://plot.ly/python/bar-charts/) etc., error bars are given as a column name which is the value of the `error_x` (for the error on x position) and `error_y` (for the error on y position).

fig.show()

import plotly.express as px

v4upgrade: true

In statistics, a [histogram](https://en.wikipedia.org/wiki/Histogram) is representation of the distribution of numerical data, where the data are binned and the count for each bin is represented. More generally, in plotly a histogram is an aggregated bar chart, with several possible aggregation functions (e.g. sum, average, count...). Also, the data to be binned can be numerical data but also categorical or date data.

See more examples of bar charts (including vertical bar charts) and styling options [here](https://plot.ly/python/bar-charts/).

[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on "tidy" data](/python/px-arguments/). For a horizontal bar char, use the `px.bar` function with `orientation='h'`.