Connecting Data Points With Smoothed Lines (Spline Curves) In Periscope With Plot.Ly (Python And R)

[intapiuser]

Ever looked at a chart like this:

and thought to yourself that the data would make much more sense with curved lined connecting the points, rather than straight lines? Well fear not, because plot.ly makes it easy to adjust this using the spline shape of line objects!

To start, let's assume the following data from a fictional gaming company is the head of our SQL output:

Then, we use either R or Python's plot.ly libraries via the Sisense for Cloud Data Teams' Python and R integration to generate our chart. Notice the reference to "spline," which gives us those nice smooth lines. (other options for connecting lines can be found on the plot.ly documentation and example here).

We've included both R and Python code below for reference. Either achieves the desired output.

R

# SQL output is imported as a dataframe variable called 'df'
# Use Sisense for Cloud Data Teams to visualize a dataframe or show text by passing data to periscope.table() or periscope.text() respectively. Show an image by calling periscope.image() after your plot.

# Use plot.ly for visualziation
library(plotly)

# Assign variables
trace <- df$count
x <- df$week
data <- df[order(df$week),]

# Check out Plot.ly's documentation to find more options! https://plot.ly/r/reference/
# The line paramater inside add_trace contains a shape parameter. Set this to spline for smoothed connectors
p <- plot_ly(data, x = ~x) %>%
  add_trace(y = ~trace, name = 'count', type = 'scatter', mode = 'lines+markers',
            line = list(shape = 'spline', color = 'rgb(205, 12, 24)', width= 4, dash = 'dash'),
            marker = list(symbol = "star-diamond", color = 'rgb(17, 157, 255)',size = 8),
            connectgaps = TRUE) %>%
  layout(xaxis = list(title = 'Week'), yaxis = list(title = 'Count'))  %>% config(displayModeBar = TRUE)

# Output the chart in Periscope
periscope.plotly(p)

Python 3.6

# SQL output is imported as a dataframe variable called 'df'
import pandas as pd
import plotly.plotly as py
import plotly.graph_objs as go

# Create trace. Notice the reference to shape in the line argument of the trace. This is set to spline, generating smoothed connectors
trace = dict(
    x = df.week,
    y = df['count'],
    mode = 'lines+markers',
    type = 'scatter',
    name = 'count',
    line = dict(shape = 'spline', color = 'rgb(205, 12, 24)', width= 4, dash = 'dash'),
    marker = dict(symbol = "star-diamond", color = 'rgb(17, 157, 255)',size = 8),
    connectgaps = True
)

# Create layout parameter to assing axes titles and set margins
layout =  dict(
    xaxis = dict(title = 'Week'),
    yaxis = dict(title = 'Count'),
    margin = dict(
        l=70,
        r=10,
        b=50,
        t=10
    )
)

# Compose the final figure
data = [trace]
fig =  go.Figure(data = data, layout = layout)

# Use Sisense for Cloud Data Teams to visualize a dataframe, text, or an image by passing data to periscope.table(), periscope.text(), or periscope.image() respectively.
periscope.plotly(fig)