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Plotly

Installation

pip install plotly

Plotly Express

  • Plotly Express is a high-level interface for creating various types of plots easily.
import plotly.express as px
fig = px.bar(x=["a", "b", "c"], y=[1, 3, 2])
fig.show()

Plotly Graph Objects

Single Plot

import plotly.graph_objects as go

# define the fig object
fig = go.Figure()
# add multiple line into the fig object
fig.add_trace(go.Scatter(x=data_train.index, y=data_train['users'], mode='lines', name='Train'))
fig.add_trace(go.Scatter(x=data_val.index, y=data_val['users'], mode='lines', name='Validation'))
fig.add_trace(go.Scatter(x=data_test.index, y=data_test['users'], mode='lines', name='Test'))
fig.update_layout(
    title  = 'Number of users',
    xaxis_title="Time",
    yaxis_title="Users",
    legend_title="Partition:",
    width=800,
    height=350,
    margin=dict(l=20, r=20, t=35, b=20),
    legend=dict(
        orientation="h",
        yanchor="top",
        y=1,
        xanchor="left",
        x=0.001
    )
)
#fig.update_xaxes(rangeslider_visible=True)
fig.show()

Subplots

  • make_subplots function from plotly.subplots is to create the subplots.
  • In the below example, make_subplots() creates the figure fig with 2 rows and 1 column.
    • fig.add_trace() function to add two traces to the figure, one for stock price data and one for volume data.
    • go.Ohlc() function creates an interactive candlestick chart based on stock price data
    • go.Scatter() function is used to plot the volume data
    • By setting layout_xaxis_rangeslider_visible to False, the update() function modifies the layout of the plot to get rid of the range slider for the x-axis.
import plotly.graph_objs as go
from plotly.subplots import make_subplots

# Define the range for cropping the x-axis
start_date = '2021-01-10'
end_date = '2021-01-20'

# Create subplots
# shared_xaxes=True to help crop both plots at the same time.
fig = make_subplots(rows=2, cols=1, shared_xaxes=True)

# Add OHLC plot at row=1, col=1
fig.add_trace(
    go.Ohlc(
        x=df["Date"],
        open=df["Open"],high=df["High"],low=df["Low"],close=df["Close"],
        name="Price"
    ),
    row=1, col=1 # specify the plot order row=1, col=1
)

# Add Volume scatter plot at row=2, col=1
fig.add_trace(
    go.Scatter(
        x=df["Date"], y=df["Volume"],
        name="Volume"
    ),
    row=2, col=1 # specify the plot order row=2, col=1
)

# Update x-axes range
fig.update_xaxes(range=[start_date, end_date])

# Hide the rangeslider
fig.update(layout_xaxis_rangeslider_visible=False)

fig.show()