pretty-plotly 0.0.1

Handy functions for easier, simpler plotting with the plotly library.

Pretty Plotly

This module provides a set of functions to create various types of plots using Plotly. It includes functions for setting the renderer, plotting scatter plots, creating traces, histograms, candlestick charts, and collections of plots.

Functions

set_renderer(renderer="plotly_mimetype+notebook")

Set the default renderer for Plotly plots.

Parameters:

• renderer (str): The name of the renderer to set as the default. Defaults to "plotly_mimetype+notebook".

Returns:

• None

Example:

import plotly.io as pio
set_renderer("notebook_connected")
print(pio.renderers.default)  # Output: notebook_connected

plot_data(x=None, y=None, z=None, size=None, colour=None, title="", colour_title="", x_label="", y_label="", name="", mode="markers", text="", fill=None, **traces)

General purpose function for plotting scatter plots in Plotly.

Parameters:

• x (list or array-like, optional): x-coordinates of the data points.
• y (list or array-like, optional): y-coordinates of the data points.
• z (list or array-like, optional): z-coordinates of the data points for 3D plots.
• size (list or array-like, optional): Sizes of the markers.
• colour (list or array-like, optional): Colors of the markers.
• title (str, optional): Title of the plot.
• colour_title (str, optional): Title of the colorbar.
• x_label (str, optional): Label for the x-axis.
• y_label (str, optional): Label for the y-axis.
• name (str, optional): Name of the trace.
• mode (str, optional): Mode of the scatter plot.
• text (list or array-like, optional): Text labels for the data points.
• fill (str, optional): Fill type for the markers.
• **traces (dict, optional): Additional traces to be added to the plot.

Returns:

• fig (plotly.graph_objects.Figure): The scatter plot figure.

Example:

import plotly.graph_objects as go

fig = plot_data(
    x=[1, 2, 3, 4],
    y=[10, 11, 12, 13],
    size=[40, 60, 80, 100],
    colour=[0, 1, 2, 3],
    title="Scatter Plot Example",
    x_label="X Axis",
    y_label="Y Axis"
)
fig.show()

create_trace(x=None, y=None, z=None, size=None, colour=None, colour_title="", name="", mode="lines", text="", fill=None)

Create a trace for a plot.

Parameters:

• x (list): x-coordinates of the trace.
• y (list): y-coordinates of the trace.
• z (list): z-coordinates of the trace (for 3D plots).
• size (int): Size of the markers.
• colour (list): Colour of the markers.
• colour_title (str): Title for the colour bar.
• name (str): Name of the trace.
• mode (str): Mode of the trace (e.g., 'lines', 'markers', 'lines+markers').
• text (list): Text associated with each marker.
• fill (str): Fill type for the trace (for area plots).

Returns:

• trace (go.Scatter or go.Scatter3d): The created trace object.

Example:

trace = create_trace(
    x=[1, 2, 3, 4],
    y=[10, 11, 12, 13],
    mode="lines+markers",
    name="Example Trace"
)
fig = go.Figure(data=[trace])
fig.show()

create_histogram(x=None, y=None, histnorm="", name="")

Create a histogram plot.

Parameters:

• x (list or array-like): Data for the x-axis.
• y (Not used in this function).
• histnorm (str): Type of normalization used for the histogram. Default is "" (no normalization).
• name (str): Name of the histogram plot.

Returns:

• go.Histogram: The histogram plot object.

Example:

hist = create_histogram(
    x=[1, 2, 2, 3, 3, 3, 4, 4, 4, 4],
    histnorm="probability",
    name="Example Histogram"
)
fig = go.Figure(data=[hist])
fig.show()

create_candle_stick(x=None, open=None, close=None, high=None, low=None, name="")

Create a candlestick chart object.

Parameters:

• x (list): List of x-axis values.
• open (list): List of opening prices.
• close (list): List of closing prices.
• high (list): List of high prices.
• low (list): List of low prices.
• name (str): Name of the candlestick chart.

Returns:

• go.Candlestick: The candlestick chart object.

Example:

candlestick = create_candle_stick(
    x=["2021-01-01", "2021-01-02", "2021-01-03"],
    open=[100, 110, 105],
    close=[110, 105, 115],
    high=[115, 120, 125],
    low=[95, 100, 105],
    name="Example Candlestick"
)
fig = go.Figure(data=[candlestick])
fig.show()

plot_collection(plots, rows=1, cols=1, title="", subplot_titles=[], x_labels={}, y_labels={}, height=1000)

Create a collection of plots arranged in a grid layout.

Parameters:

• plots (dict): A dictionary containing the plots to be added to the collection. The keys represent the position of the plot in the grid (row, col), and the values are instances of the Plot class.
• rows (int): The number of rows in the grid layout. Default is 1.
• cols (int): The number of columns in the grid layout. Default is 1.
• title (str): The title of the plot collection. Default is an empty string.
• subplot_titles (list): A list of titles for each subplot. The length of the list should be equal to the number of subplots. Default is an empty list.
• x_labels (dict): A dictionary mapping the position of each subplot to its x-axis label. Default is an empty dictionary.
• y_labels (dict): A dictionary mapping the position of each subplot to its y-axis label. Default is an empty dictionary.
• height (int): The height of the plot collection in pixels. Default is 1000.

Returns:

• fig (plotly.graph_objects.Figure): The plotly figure object representing the plot collection.

Example:

scatter_plot = plot_data(
    x=[1, 2, 3],
    y=[4, 5, 6],
    title="Scatter Plot",
    x_label="X Axis",
    y_label="Y Axis"
)

histogram = create_histogram(
    x=[1, 2, 2, 3, 3, 3, 4, 4, 4, 4],
    name="Histogram"
)

plots = {
    (1, 1): scatter_plot,
    (1, 2): histogram
}

fig = plot_collection(
    plots=plots,
    rows=1,
    cols=2,
    title="Plot Collection",
    subplot_titles=["Scatter Plot", "Histogram"]
)
fig.show()