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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('https://raw.githubusercontent.com/plotly/datasets/master/2014_apple_stock.csv')
df.head()
Out[1]:
AAPL_x AAPL_y
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 plotly.express as px

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_apple_stock.csv')

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

Plot from CSV with graph_objects

In [3]:
import pandas as pd
import plotly.graph_objects as go

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_apple_stock.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)',
                   showlegend=True)

fig.show()

Reference

See https://plotly.com/python/getting-started 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 https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), 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 plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

import dash
import dash_core_components as dcc
import dash_html_components as html

app = dash.Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

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