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GeezerVison is showing plotly.com — Table and chart subplots in Python Import CSV Data¶In [1]:
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! 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 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
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