Plot CSV Data in Python

How to create charts from csv files with Plotly and Python

New to Plotly?

Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

CSV or comma-delimited-values is a very popular format for storing structured data. In this tutorial, we will see how to plot beautiful graphs using csv data, and Pandas. We will learn how to import csv data from an external source (a url), and plot it using Plotly and pandas.

First we import the data and look at it.

In [1]:
import pandas as pd
df = pd.read_csv('')
0 2014-01-02 77.445395
1 2014-01-03 77.045575
2 2014-01-06 74.896972
3 2014-01-07 75.856461
4 2014-01-08 75.091947

Plot from CSV with Plotly Express

In [2]:
import pandas as pd
import as px

df = pd.read_csv('')

fig = px.line(df, x = 'AAPL_x', y = 'AAPL_y', title='Apple Share Prices over time (2014)')

Plot from CSV 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

Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.


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Plot from CSV with graph_objects

In [4]:
import pandas as pd
import plotly.graph_objects as go

df = pd.read_csv('')

fig = go.Figure(go.Scatter(x = df['AAPL_x'], y = df['AAPL_y'],
                  name='Share Prices (in USD)'))

fig.update_layout(title='Apple Share Prices over time (2014)',
                   plot_bgcolor='rgb(230, 230,230)',


See for more information about Plotly's Python API!

What About Dash?

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at

Everywhere in this page that you see, you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or as px
fig = go.Figure() # or any Plotly Express function e.g.
# fig.add_trace( ... )
# fig.update_layout( ... )

from dash import Dash, dcc, html

app = Dash()
app.layout = html.Div([

app.run_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter