bumpy_chart.md

Bumpy Charts

Content

• Overview
• Documentation
• Examples

Overview

• Bumpy Chart or Bump Chart is used to compare two dimensions against each other using one of the Measure value.

• They are very useful for exploring the changes in Rank of a value over a time dimension or place dimension or some other dimension relevant to the analysis.

• Using soccerplots package one can easily build a bumpy chart, here we will look into the documentation and some examples that will help user to create bumpy charts.

soccerplots.bumpy_chart.Bumpy

soccerplots.bumpy_chart.Bumpy(
    background_color="#1B1B1B", scatter_color="#4F535C", scatter_points='o', scatter_size=100,
    ticklabel_size=13, fontfamily="Liberation Serif", curviness=0.85,
    rotate_xticks=0, rotate_yticks=0, show_right=False, label_size=20, labelpad=20, horizontalalignment_x='left',
    horizontalalignment_y='right', alignment_xvalue=0.035, alignment_yvalue=0.16, label_color='#FFFFFF', 
    plot_labels=True
)

No.	Parameter	About Parameter
1.	background_color	(str, optional) background color for the plot. Defaults to "#1B1B1B".
2.	scatter_color	(str, optional) color value for our scater points. Defaults to "#4F535C".
3.	scatter_points	(str, optional) type of scatter point user wants to plot. Defaults to 'o'.
4.	scatter_size	(float, optional) size of the scatter_points. Defaults to 100.
5.	ticklabel_size	(float, optional) fontsize of the ticklabel. Defaults to 13.
6.	fontfamily	(str, optional) fontfamily available in matplotlib. Defaults to "Liberation Serif".
7.	curviness	(float, optional) value of the curved line. Defaults to 0.85.
8.	rotate_xticks	(int, optional) rotation of xticklabels in degrees. Defaults to 0.
9.	rotate_yticks	(int, optional) rotation of yticklabels. Defaults to 0.
10.	show_right	(bool, optional) yticklabels to be shown at the right y-axis or not. Defaults to False.
11.	label_size	(int, optional) fontsize of the x and y labels. Defaults to 20.
12.	labelpad	(int, optional) padding between labels and ticklables. Defaults to 20.
11.	horizontalalignment_x	(str, optional) alignment for the x-label. Defaults to 'left'.
12.	horizontalalignment_y	(str, optional) alignment for the y-label. Defaults to 'right'.
13.	alignment_xvalue	(float, optional) value for alignment of x-label. Defaults to 0.035.
14.	alignment_yvalue	(float, optional) value for alignment of y-label. Defaults to 0.16.
15.	label_color	(str, optional) color value for labels. Defaults to '#FFFFFF'.
16.	plot_labels	(bool, optional): to plot the labels. Defaults to True.

soccerplots.bumpy_chart.Bumpy.plot

soccerplots.bumpy_chart.Bumpy.plot(
     x_list, y_list, values, highlight_dict, filename=None, dpi=300, figsize=(12,8), lw=2, show=True, 
     x_label=None, y_label=None, title=None, title_dict=None, xy=None, title_color="#FFFFFF", title_size=25, 
     endnote=None, xy_end=None, end_color="#808080", end_size=15, image=None, image_coord=None, alpha=1, 
     interpolation="none", xlim=None, ylim=None, figax=None, **kwargs
)

No.	Parameter	About Parameter
1.	x_list	(list) xticklabel values(serial-wise order from left to right).
2.	y_list	(list) yticklabel values(serial-wise order from top to bottom).
3.	values	(dict) containing key as team-name and value as list of rank for that team.
4.	highlight_dict	(dict) containing key as the team-name to be highlighted with their corresponding color.
5.	filename	(str, optional) the name of the file per which plot will be saved. Defaults to None.
6.	dpi	(int, optional) dots per inch value. Defaults to 300.
7.	figsize	(tuple, optional) size of the plot. Defaults to (12,8).
8.	lw	(int, optional) line-width for the lines in the plot. Defaults to 2.
9.	show	(bool, optional) whether to display the plot or not. Defaults to True.
10.	x_label	(str, optional) x-label-name. Defaults to None.
11.	y_label	(str, optional) y-label-name. Defaults to None.
12.	title	(str, optional) the title of the plot. Defaults to None.
13.	title_dict	(dict, optional) extra information about title. Defaults to None.
14.	xy	(tuple, optional) x and y coordinate for the title. Defaults to None.
15.	title_color	(str, optional) color value for title. Defaults to "#FFFFFF".
16.	title_size	(float, optional) size of the title. Defaults to 25.
17.	endnote	(str, optional) the endnote of the plot. Defaults to None.
18.	xy_end	(tuple, optional) x and y coordinate for endnote. Defaults to None.
19.	end_color	(str, optional) color value for the endnote. Defaults to "#808080".
20.	end_size	(float, optional) size of endnote. Defaults to 15.
21.	image	(str, optional) path of the image to be added. Defaults to None.
22.	image_coord	(list, optional) containing left, bottom, width, height for image. Defaults to None.
23.	alpha	(float, optional) the alpha value for the image. Defaults to 1.
24.	interpolation	(str, optional) interpolation for the image. Defaults to "none".
25.	xlim	(tuple, optional) limit for x axis value. Defaults to None.
26.	ylim	(tuple, optional) limit for y axis value. Defaults to None.
27.	figax	(tuple, optional) figure and axis object. Defaults to None.

No.	Returns	About
1.	fig	(matplotlib.Figure.figure) figure object
2.	ax	(axes.Axes) axis object

Examples

• Here we will look into some of the examples that can help in making bump-charts using soccerplots.

• Examples Content:

  • Making a simple Bump Chart
  • Changing ticklables and labels size
  • Adding title
  • Title color
  • Adding Image
  • Adjust alpha for image
  • Change scatter points
  • Show labels on right side
  • Aligning Labels
  • Changing Theme
  • Labelpad
  • Changing Font
  • Adding Endnote
  • Saving The Plot
  • Some More Examples

Making a simple Bump Chart

• Here we will make a simple bump-chart, comparing the weekwise standing of Premier League teams in 2019/20 season.

• And will highlight out Man City with skyblue color, Liverpool with crimson color and Man Utd with gold color.

• Data here (scrapped from transfermarkt).

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man City": "skyblue", "Liverpool": "crimson", "Man Utd": "gold"}

## instantiate object
bumpy = Bumpy(rotate_xticks=90)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position'
)

• Output:

Changing ticklables and labels size

• One can pass ticklabel_size and label_size to change the fontsize for ticklables and labels.

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man City": "skyblue", "Liverpool": "crimson", "Man Utd": "gold"}

## instantiate object
bumpy = Bumpy(rotate_xticks=90, ticklabel_size=17, label_size=30)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position'
)

• Output:

Adding title

• Bumpy.plot method uses soccerplots.utils.plot_text method to plot title.

• So the user have to pass text(i.e. title) and text_dict(i.e. dict specifying which word to modify).

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man City": "skyblue", "Liverpool": "crimson", "Man Utd": "gold"}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Liverpool, Man_City and Man_Utd"""

## title info
title_dict = {
    "Liverpool,": dict(color="crimson", ignore_last=True),
    "Man_City": dict(color="skyblue", ignore=True),
    "Man_Utd": dict(color="gold", ignore=True)
}

## instantiate object
bumpy = Bumpy(rotate_xticks=90, ticklabel_size=17, label_size=30)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(12.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5]
)

• Output:

Title color

• title_color argument is the default color for the title if title_dict is not passed it will use that color. It is also the same color for the rest of the words that are not specified in the title_dict.

• Note: If the title wont show in the plot try adjusting ylim in plot method as shown below.

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man City": "skyblue", "Liverpool": "crimson", "Man Utd": "gold"}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Liverpool, Man_City and Man_Utd"""

## title info
title_dict = {
    "Liverpool,": dict(color="crimson", ignore_last=True),
    "Man_City": dict(color="skyblue", ignore=True),
    "Man_Utd": dict(color="gold", ignore=True)
}

## instantiate object
bumpy = Bumpy(rotate_xticks=90, ticklabel_size=17, label_size=30)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(12.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5],
    title_color="grey"
)

• Output:

Adding Image

• The user can pass image and image_coord to the plot method to plot an image.

• Note: If the image wont show in the plot try adjusting ylim in plot method as shown below.

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man City": "skyblue", "Liverpool": "crimson", "Man Utd": "gold"}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Liverpool, Man_City and Man_Utd"""

## title info
title_dict = {
    "Liverpool,": dict(color="crimson", ignore_last=True),
    "Man_City": dict(color="skyblue", ignore=True),
    "Man_Utd": dict(color="gold", ignore=True)
}

## instantiate object
bumpy = Bumpy(rotate_xticks=90, ticklabel_size=17, label_size=30)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(16.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5],
    image="epl.png", image_coord=[0.135, 0.8, 0.1, 0.1]
)

• Output:

Adjust alpha for image

• To control the transparency of the image pass alpha argument to plot method.

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man City": "skyblue", "Liverpool": "crimson", "Man Utd": "gold"}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Liverpool, Man_City and Man_Utd"""

## title info
title_dict = {
    "Liverpool,": dict(color="crimson", ignore_last=True),
    "Man_City": dict(color="skyblue", ignore=True),
    "Man_Utd": dict(color="gold", ignore=True)
}

## instantiate object
bumpy = Bumpy(rotate_xticks=90, ticklabel_size=17, label_size=30)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(16.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5],
    image="epl.png", image_coord=[0.135, 0.8, 0.1, 0.1], alpha=0.7
)

• Output:

Change scatter points

• The user can also change the scatter points style. Default is a circle.

• Visit here to see all available styles.

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man City": "skyblue", "Liverpool": "crimson", "Man Utd": "gold"}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Liverpool, Man_City and Man_Utd"""

## title info
title_dict = {
    "Liverpool,": dict(color="crimson", ignore_last=True),
    "Man_City": dict(color="skyblue", ignore=True),
    "Man_Utd": dict(color="gold", ignore=True)
}

## instantiate object
bumpy = Bumpy(scatter_points="D", rotate_xticks=90, ticklabel_size=17, label_size=30)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(16.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5],
    image="epl.png", image_coord=[0.135, 0.8, 0.1, 0.1]
)

• Output:

Show labels on right side

• To show the y-ticklables on right-side, the user can pass show_right=True.

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man City": "skyblue", "Liverpool": "crimson", "Man Utd": "gold"}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Liverpool, Man_City and Man_Utd"""

## title info
title_dict = {
    "Liverpool,": dict(color="crimson", ignore_last=True),
    "Man_City": dict(color="skyblue", ignore=True),
    "Man_Utd": dict(color="gold", ignore=True)
}

## instantiate object
bumpy = Bumpy(scatter_points="D", rotate_xticks=90, ticklabel_size=17, label_size=30,
            show_right=True)
            
## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(16.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5],
    image="epl.png", image_coord=[0.135, 0.8, 0.1, 0.1]
)

• Output:

Aligning Labels

• To change the position of the x-lables and y-labels the user can use alignment_xvalue and alignment_yvalue parameters.

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man City": "skyblue", "Liverpool": "crimson", "Man Utd": "gold"}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Liverpool, Man_City and Man_Utd"""

## title info
title_dict = {
    "Liverpool,": dict(color="crimson", ignore_last=True),
    "Man_City": dict(color="skyblue", ignore=True),
    "Man_Utd": dict(color="gold", ignore=True)
}

## instantiate object
bumpy = Bumpy(scatter_points="D", rotate_xticks=90, ticklabel_size=17, label_size=30,
            show_right=True, alignment_xvalue=0.44, alignment_yvalue=0.44)
            
## plot bumpy chart            
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(16.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5],
    image="epl.png", image_coord=[0.135, 0.8, 0.1, 0.1]
)

• Output:

Changing Theme

• The default theme is a dark one, but the user have the access to change it.

• One can pass background_color, scatter_color, label_color arguments.

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man Utd": "crimson", "Chelsea": "blue"}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Man_Utd and Chelsea"""

## title info
title_dict = {
    "Man_Utd": dict(color="crimson", ignore=True),
    "Chelsea": dict(color="blue")
}

## instantiate object
bumpy = Bumpy(background_color="#FFFFFF", scatter_color="grey", label_color="#000000",
              scatter_points="D", rotate_xticks=90, ticklabel_size=17, 
              label_size=30,show_right=True)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(12.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5],
    title_color="#121212"
)

• Output:

Labelpad

• To increase or decrease the distance between labels and ticklabels one can use labelpad argument.

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man Utd": "crimson", "Chelsea": "skyblue"}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Man_Utd and Chelsea"""

## title info
title_dict = {
    "Man_Utd": dict(color="crimson", ignore=True),
    "Chelsea": dict(color="skyblue")
}

## instantiate object
bumpy = Bumpy(scatter_points="D", rotate_xticks=90, ticklabel_size=17, 
              label_size=30,show_right=True, labelpad=45)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(12.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5]
)

• Output:

Changing Font

• To change the font pass fontfamily argument to Bumpy.

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man Utd": "crimson", "Chelsea": "skyblue"}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Man_Utd and Chelsea"""

## title info
title_dict = {
    "Man_Utd": dict(color="crimson", ignore=True),
    "Chelsea": dict(color="skyblue")
}

## instantiate object
bumpy = Bumpy(scatter_points="D", rotate_xticks=90, ticklabel_size=17, 
              label_size=30,show_right=True, fontfamily="Ubuntu")

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(12.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5]
)

• Output:

Adding Endnote

• To add endnote pass endnote argument to plot method.

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man Utd": "crimson", "Chelsea": "skyblue"}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Man_Utd and Chelsea"""

## title info
title_dict = {
    "Man_Utd": dict(color="crimson", ignore=True),
    "Chelsea": dict(color="skyblue")
}

## endnote
endnote = """Created using soccerplots
Visualization by: Anmol Durgapal(@slothfulwave612)"""

## instantiate object
bumpy = Bumpy(scatter_points="D", rotate_xticks=90, ticklabel_size=17, 
              label_size=30,show_right=True)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(12.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5],
    endnote=endnote
)

• Output:

• Note: One can also make use of end_color and end_size in plot method to change color and size of the endnote respectively.

Saving The Plot

• Use filename and dpi arguments to save the file.

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"Man Utd": "crimson", "Chelsea": "skyblue"}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Man_Utd and Chelsea"""

## title info
title_dict = {
    "Man_Utd": dict(color="crimson", ignore=True),
    "Chelsea": dict(color="skyblue")
}

## endnote
endnote = """Created using soccerplots
Visualization by: Anmol Durgapal(@slothfulwave612)"""

## instantiate object
bumpy = Bumpy(scatter_points="D", rotate_xticks=90, ticklabel_size=17, 
              label_size=30,show_right=True)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(12.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5],
    filename="my_bumpy.jpg", dpi=500
)

• Output:

Some More Examples

• Content:
  • Example 01
  • Example 02
  • Example 03
  • Example 04
  • Example 05
  • Example 06

Example 01

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("la_liga.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {"FC Barcelona": "skyblue", "Real Madrid": "#D4AF37"}

## title 
title = """La Liga 2019/20 week-wise standings:
A comparison between FC_Barcelona and Real_Madrid"""

## title info
title_dict = {
    "FC_Barcelona": dict(color="skyblue", ignore=True),
    "Real_Madrid": dict(color="#D4AF37", ignore=True)
}

## endnote
endnote = "visualization made by Anmol Durgapal(@slothfulwave612)"

## instantiate object
bumpy = Bumpy(scatter_points="D", rotate_xticks=90, ticklabel_size=17, label_size=30,
            show_right=True)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(15, 21.5), ylim=(-0.1, 23), title_size=[30,22.5],
    image="laliga.png", image_coord=[0.135, 0.805, 0.1, 0.1], endnote=endnote
)

• Output:

Example 02

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("la_liga.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {
    "Atlético Madrid": "crimson", "Sevilla FC": "gold", "Real Sociedad": "skyblue"
}

## title 
title = """La Liga 2019/20 week-wise standings:
A comparison between Atlético_Madrid, Sevilla_FC and Real_Sociedad"""

## title info
title_dict = {
    "Atlético_Madrid,": dict(color="crimson", ignore=True, ignore_last=True),
    "Sevilla_FC": dict(color="gold", ignore=True),
    "Real_Sociedad": dict(color="skyblue", ignore=True)
}

## endnote
endnote = "visualization made by Anmol Durgapal(@slothfulwave612)"

## instantiate object
bumpy = Bumpy(scatter_points="o", rotate_xticks=90, ticklabel_size=17, label_size=30,
            show_right=True)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(17.5, 21.5), ylim=(-0.1, 23), title_size=[30,22.5],
    image="laliga.png", image_coord=[0.135, 0.805, 0.1, 0.1], endnote=endnote
)

• Output:

Example 03

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data: http:https://bit.do/data_epl
season_dict = json.load(open("epl.json"))

## match-week and highlight dict
match_day = ["Week " + str(num) for num in range(1, 39)]
team_dict = {
    "Man Utd": "#907E46", "Chelsea": "skyblue"
}

## title 
title = """Premier League 2019/20 week-wise standings:
A comparison between Man_Utd and Chelsea"""

## title info
title_dict = {
    "Man_Utd": dict(color="#907E46", ignore=True),
    "Chelsea": dict(color="skyblue"),
}

## endnote
endnote = "visualization made by Anmol Durgapal(@slothfulwave612)"

## instantiate object
bumpy = Bumpy(scatter_points="D", rotate_xticks=90, ticklabel_size=17, label_size=30,
            show_right=True)

## plot bumpy chart
fig, ax = bumpy.plot(
    x_list=match_day, y_list=list(range(1, 21)), values=season_dict, 
    highlight_dict=team_dict, figsize=(20,16), x_label='Week', y_label='Position',
    title=title, title_dict=title_dict, xy=(17, 21.5), ylim=(-0.1, 23), title_size=[30,22.5],
    image="epl.png", image_coord=[0.135, 0.805, 0.1, 0.1], endnote=endnote
)

• Output:

Example 04

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data:  http:https://bit.do/data_ucl
season_dict = json.load(open("ucl.json"))

## season names
season = [
    '03/04',
    '04/05',
    '05/06',
    '06/07',
    '07/08',
    '08/09',
    '09/10',
    '10/11',
    '11/12',
    '12/13',
    '13/14',
    '14/15',
    '15/16',
    '16/17',
    '17/18',
    '18/19',
    '19/20'
]

## position names
position = [
    'Winner',
    'Runner-Up',
    'Semi-Final',
    'Quarter-Final',
    'RO16',
    'Group-Stage',
    'Not-Eligible'
]

## title
text = """At which stage did the teams finished their UCL Campaign(2003-2020)
A comparison between Real_Madrid and Barcelona"""

## endnote
endnote = "visualization made by Anmol Durgapal(@slothfulwave612)"

## title dict
text_dict = {
    "Real_Madrid": dict(color="#D4AF37", ignore=True),
    "Barcelona": dict(color="skyblue")
}

## highlight dict
hdict = {
    "Real Madrid": "#D4AF37", "Barcelona": "skyblue"
}

## instantiate object
rank = Bumpy(scatter_color='#38393B', rotate_xticks=90, ticklabel_size=17, 
             label_size=30, show_right=True)

## plot bumpy chart
fig, ax = rank.plot(
    season, position, season_dict, 
    highlight_dict=hdict, figsize=(16,12),
    x_label='Season', y_label='Position', image='ucl.png', image_coord=[0.13, 0.715, 0.1, 0.2],
    title=text, xy=(10.4, 7.8), title_dict=text_dict, title_size = [24, 22],
    endnote=endnote, xy_end=(len(season)+1.6, -1.5), end_size=17, ylim=(0, 9)
)

• Output:

Example 05

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data:  http:https://bit.do/data_ucl
season_dict = json.load(open("ucl.json"))

## season names
season = [
    '03/04',
    '04/05',
    '05/06',
    '06/07',
    '07/08',
    '08/09',
    '09/10',
    '10/11',
    '11/12',
    '12/13',
    '13/14',
    '14/15',
    '15/16',
    '16/17',
    '17/18',
    '18/19',
    '19/20'
]

## position names
position = [
    'Winner',
    'Runner-Up',
    'Semi-Final',
    'Quarter-Final',
    'RO16',
    'Group-Stage',
    'Not-Eligible'
]

## title
text = """At which stage did the teams finished their UCL Campaign(2003-2020)
A comparison between Chelsea and Man_Utd"""

## endnote
endnote = "visualization made by Anmol Durgapal(@slothfulwave612)"

## title dict
text_dict = {
    "Man_Utd": dict(color="crimson", ignore=True),
    "Chelsea": dict(color="skyblue")
}

## highlight dict
hdict = {
    "Man Utd": "crimson", "Chelsea": "skyblue"
}

## instantiate object
rank = Bumpy(scatter_color='#38393B', rotate_xticks=90, ticklabel_size=17, 
             label_size=30, show_right=True)

## plot bumpy chart
fig, ax = rank.plot(
    season, position, season_dict, 
    highlight_dict=hdict, figsize=(16,12),
    x_label='Season', y_label='Position', image='ucl.png', image_coord=[0.13, 0.715, 0.1, 0.2],
    title=text, xy=(10.4, 7.8), title_dict=text_dict, title_size = [24, 22],
    endnote=endnote, xy_end=(len(season)+1.6, -1.5), end_size=17, ylim=(0, 9)
)

• Output:

Example 06

• Code Snippet:

import json
from soccerplots.bumpy_chart import Bumpy

## load the data:  http:https://bit.do/data_ucl
season_dict = json.load(open("ucl.json"))

## season names
season = [
    '03/04',
    '04/05',
    '05/06',
    '06/07',
    '07/08',
    '08/09',
    '09/10',
    '10/11',
    '11/12',
    '12/13',
    '13/14',
    '14/15',
    '15/16',
    '16/17',
    '17/18',
    '18/19',
    '19/20'
]

## position names
position = [
    'Winner',
    'Runner-Up',
    'Semi-Final',
    'Quarter-Final',
    'RO16',
    'Group-Stage',
    'Not-Eligible'
]

## title
text = """At which stage did the teams finished their UCL Campaign(2003-2020)
A comparison between Liverpool and Man_Utd"""

## endnote
endnote = "visualization made by Anmol Durgapal(@slothfulwave612)"

## title dict
text_dict = {
    "Man_Utd": dict(color="#907E46", ignore=True),
    "Liverpool": dict(color="crimson")
}

## highlight dict
hdict = {
    "Man Utd": "#907E46", "Liverpool": "crimson"
}

## instantiate object
rank = Bumpy(scatter_points='D', scatter_color='#38393B', rotate_xticks=90, ticklabel_size=17, 
             label_size=30, show_right=True)

## plot bumpy chart
fig, ax = rank.plot(
    season, position, season_dict, 
    highlight_dict=hdict, figsize=(16,12),
    x_label='Season', y_label='Position', image='ucl.png', image_coord=[0.13, 0.715, 0.1, 0.2],
    title=text, xy=(10.4, 7.8), title_dict=text_dict, title_size = [24, 22],
    endnote=endnote, xy_end=(len(season)+1.6, -1.5), end_size=17, ylim=(0, 9)
)

• Output:

---