Plot CSV Data in Python
How to create charts from csv files with Plotly and Python
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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.
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_apple_stock.csv')
df.head()
Plot from CSV with Plotly Express¶
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 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 & deploy apps like this with Dash Enterprise.
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Plot from CSV with graph_objects
¶
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=dict(text='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( ... )
from dash import Dash, dcc, html
app = Dash()
app.layout = html.Div([
dcc.Graph(figure=fig)
])
app.run(debug=True, use_reloader=False) # Turn off reloader if inside Jupyter
