Line Charts in Python

How to make line charts in Python with Plotly. Examples on creating and styling line charts in Python with Plotly.

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Line Plots with plotly.express¶

Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures. With px.line, each data point is represented as a vertex (which location is given by the x and y columns) of a polyline mark in 2D space.

For more examples of line plots, see the line and scatter notebook.

In [1]:

import plotly.express as px

df = px.data.gapminder().query("country=='Canada'")
fig = px.line(df, x="year", y="lifeExp", title='Life expectancy in Canada')
fig.show()

Line Plots with column encoding color¶

In [2]:

import plotly.express as px

df = px.data.gapminder().query("continent=='Oceania'")
fig = px.line(df, x="year", y="lifeExp", color='country')
fig.show()

Line charts in Dash¶

Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash, click "Download" to get the code and run python app.py.

Get started with the official Dash docs and learn how to effortlessly style & publish apps like this with Dash Enterprise or Plotly Cloud.

Out[3]:

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Data Order in Line Charts¶

Plotly line charts are implemented as connected scatterplots (see below), meaning that the points are plotted and connected with lines in the order they are provided, with no automatic reordering.

This makes it possible to make charts like the one below, but also means that it may be required to explicitly sort data before passing it to Plotly to avoid lines moving "backwards" across the chart.

In [4]:

import plotly.express as px
import pandas as pd

df = pd.DataFrame(dict(
    x = [1, 3, 2, 4],
    y = [1, 2, 3, 4]
))
fig = px.line(df, x="x", y="y", title="Unsorted Input")
fig.show()

df = df.sort_values(by="x")
fig = px.line(df, x="x", y="y", title="Sorted Input")