on - edited on by
DRay
Here's a script that takes a data frame with two values, the current and benchmark, and returns radial bar charts to plot progress toward a goal. You can also choose a color using the color_theme parameter that takes values 'Grey', 'Purple, 'Blue', 'Green', 'Orange', or 'Red'.
Reason to use it:
One of the most common questions an analyst is asked is how close am I to a goal? We had a great thread about doing this in a variety of ways here. The most common tool that people default to on these is to use a gauge chart, which albeit feeling familiar with driving a car, is not necessarily appropriate for visually encoding in an elegant way.
With Python in Sisense for Cloud Data Teams, we can start to create custom chart types that are awesome and fit use-cases perfectly. The biggest issue with gauge charts is when you go beyond 100%, do you loop back to the beginning of the gauge or just adjust where 100% is? If we take a step back and look at how the visual could work, we can assemble a few radial components into a full 360° = 100%. That way, when we want a 200%, we can just have multiple 360° rings.
#######################################################################
### LIBRARIES ###
#######################################################################
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
#######################################################################
### HELPER FUNCTIONS ###
#######################################################################
#USE: Create an array structure for rings.
#INPUT: a df of row length 1 with the first column as the current metric value and the second colum is the target metric value
#OUTPUT: an aray of arrays representing each ring
def calculate_rings(df):
if df.iloc[0,0] < df.iloc[0,1]:
rings=[[df.iloc[0,0],df.iloc[0,1]-df.iloc[0,0]],[0,0]]
elif df.iloc[0,0] / df.iloc[0,1] < 2:
rings=[[df.iloc[0,0],0],[df.iloc[0,0] % df.iloc[0,1], df.iloc[0,1]-df.iloc[0,0] % df.iloc[0,1]]]
else:
rings = [[0,0],[0,0]]
return rings
#USE: Determine if the label for the rotating number label should be left/center/right
#INPUT: a df of row length 1 with the first column as the current metric value and the second colum is the target metric value
#OUTPUT: the proper text alignment
def horizontal_aligner(df):
metric = 1.0 * df.iloc[0,0] % df.iloc[0,1] / df.iloc[0,1]
if metric in (0, 0.5):
align = 'center'
elif metric < 0.5:
align = 'left'
else:
align = 'right'
return align
def vertical_aligner(df):
metric = 1.0 * df.iloc[0,0] % df.iloc[0,1] / df.iloc[0,1]
if metric < 0.25:
align = 'bottom'
elif metric < 0.75:
align = 'top'
elif metric > 0.75:
align = 'bottom'
else:
align = 'center'
return align
#USE: Create a center label in the middle of the radial chart.
#INPUT: a df of row length 1 with the first column as the current metric value and the second column is the target metric value
#OUTPUT: the proper text label
def add_center_label(df):
percent = str(round(1.0*df.iloc[0, 0]/df.iloc[0, 1]*100,1)) + '%'
return plt.text(0,
0.2,
percent,
horizontalalignment='center',
verticalalignment='center',
fontsize = 40,
family = 'sans-serif')
#USE: Formats a number with the apropiate currency tags.
#INPUT: a currency number
#OUTPUT: the properly formmated currency string
def get_currency_label(num):
currency = ''
if num < 10**3:
currency = '$' + str(num)
elif num < 10**6:
currency = '$' + str(round(1.0*num/10**3,1)) + 'K'
elif df.iloc[0,0] < 10**9:
currency = '$' + str(round(num/10**6,1)) + 'M'
else:
currency = '$' + str(round(num/10**9,1)) + 'B'
return currency
#USE: Create a dynamic outer label that servers a pointer on the ring.
#INPUT: a df of row length 1 with the first column as the current metric value and the second column is the target metric value
#OUTPUT: the proper text label at the apropiate position
def add_current_label(df):
currency = get_currency_label(df.iloc[0,0])
print('vertical: ' + vertical_aligner(df))
print('horizontal: ' + horizontal_aligner(df))
return plt.text(1.5 * np.cos(0.5 *np.pi - 2 * np.pi * (float(df.iloc[0,0]) % df.iloc[0,1] /df.iloc[0,1])),
1.5 * np.sin(0.5 *np.pi - 2 * np.pi * (float(df.iloc[0,0]) % df.iloc[0,1] / df.iloc[0,1])),
currency,
horizontalalignment=horizontal_aligner(df),
verticalalignment=vertical_aligner(df),
fontsize = 20,
family = 'sans-serif')
def add_sub_center_label(df):
amount = 'Goal: ' + get_currency_label(df.iloc[0,1])
return plt.text(0,
-.1,
amount,
horizontalalignment='center',
verticalalignment='top',
fontsize = 22,family = 'sans-serif')
#######################################################################
### MAIN FUNCTION ###
#######################################################################
def create_radial_chart(df, color_theme = 'Purple'):
# base styling logic
color = plt.get_cmap(color_theme + 's')
ring_width = 0.3
outer_radius = 1.5
inner_radius = outer_radius - ring_width
# set up plot
ring_arrays = calculate_rings(df)
fig, ax = plt.subplots()
if df.iloc[0, 0] > df.iloc[0, 1]:
ring_to_label = 0
outer_edge_color = None
inner_edge_color = 'white'
else:
ring_to_label = 1
outer_edge_color, inner_edge_color = ['white', None]
# plot logic
outer_ring, _ = ax.pie(ring_arrays[0],radius=1.5,
colors=[color(0.9), color(0.15)],
startangle = 90,
counterclock = False)
plt.setp( outer_ring, width=ring_width, edgecolor=outer_edge_color)
inner_ring, _ = ax.pie(ring_arrays[1],
radius=inner_radius,
colors=[color(0.55), color(0.05)],
startangle = 90,
counterclock = False)
plt.setp(inner_ring, width=ring_width, edgecolor=inner_edge_color)
# add labels and format plots
add_center_label(df)
add_current_label(df)
add_sub_center_label(df)
ax.axis('equal')
plt.margins(0,0)
plt.autoscale('enable')
return plt
# call the chart maker function and display the chart
periscope.output(create_radial_chart(df, color_theme='Purple'))
# Currently supported color themes: Grey, Purple, Blue, Green, Orange, Red
An additional layer of information can be introduced using a subtitle below the percentage. Thanks to Kyle Dempsey for developing a simple function to do this. Here's the code with an adjusted position of the percent and subtitle.
def add_center_label(df):
percent = str(round(1.0*df.iloc[0, 0]/df.iloc[0, 1]*100)) + '%'
return plt.text(0,
0.2,
percent,
horizontalalignment='center',
verticalalignment='center',
fontsize = 40,
family = 'sans-serif')
def add_sub_center_label(df):
amount = 'Goal: ' + get_currency_label(df.iloc[0,1])
return plt.text(0,
-0.1,
amount,
horizontalalignment='center',
verticalalignment='top',
fontsize = 22,family = 'sans-serif')
