Table and Chart Subplots in Python
How to create a subplot with tables and charts in Python with Plotly.
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.
Import CSV Data¶
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import pandas as pd
import re
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/Mining-BTC-180.csv")
for i, row in enumerate(df["Date"]):
p = re.compile(" 00:00:00")
datetime = p.split(df["Date"][i])[0]
df.iloc[i, 1] = datetime
fig = make_subplots(
rows=3, cols=1,
shared_xaxes=True,
vertical_spacing=0.03,
specs=[[{"type": "table"}],
[{"type": "scatter"}],
[{"type": "scatter"}]]
)
fig.add_trace(
go.Scatter(
x=df["Date"],
y=df["Mining-revenue-USD"],
mode="lines",
name="mining revenue"
),
row=3, col=1
)
fig.add_trace(
go.Scatter(
x=df["Date"],
y=df["Hash-rate"],
mode="lines",
name="hash-rate-TH/s"
),
row=2, col=1
)
fig.add_trace(
go.Table(
header=dict(
values=["Date", "Number<br>Transactions", "Output<br>Volume (BTC)",
"Market<br>Price", "Hash<br>Rate", "Cost per<br>trans-USD",
"Mining<br>Revenue-USD", "Trasaction<br>fees-BTC"],
font=dict(size=10),
align="left"
),
cells=dict(
values=[df[k].tolist() for k in df.columns[1:]],
align = "left")
),
row=1, col=1
)
fig.update_layout(
height=800,
showlegend=False,
title_text="Bitcoin mining stats for 180 days",
)
fig.show()
Reference¶
See https://plotly.com/python/reference/table/ for more information regarding chart attributes!
For examples of Plotly Tables, see: https://plotly.com/python/table/
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_server(debug=True, use_reloader=False) # Turn off reloader if inside Jupyter