Assigning Different Colors to Each plt.step Line

Understanding the Problem

The provided code uses matplotlib’s plt.step() function to plot lines connecting points for each team according to their tournament position in each game week. However, there are two issues with the current implementation:

1. A fourth line (violet) is drawn, which is not intended and seems to be an artifact of the grouping operation.
2. The lines are drawn from x = 0, but they should be aligned with the points (which are correctly drawn), starting from x = 1.

Why is a Fourth Line Drawn?

The fourth line appears to be a result of the way plt.step() handles grouping and iteration over the data. When using groupby() in combination with plt.step(), matplotlib attempts to plot lines between consecutive points within each group. However, it also draws an additional line that represents the entire range of x values for each group.

In this case, since there are only three unique teams (Team1, Team2, and Team3), the fourth line is essentially the cumulative sum of the positions for all teams across all game weeks. This can be seen as a result of plt.step() trying to connect every point in the data, rather than just the points within each group.

Why are Lines Drawn from x = 0?

The issue with lines being drawn from x = 0 instead of x = 1 is likely due to how matplotlib handles x-axis limits. By default, plt.xlim() sets the minimum and maximum values for the x-axis; however, it does not directly control where the tick marks or labels are placed.

To align the lines with the points (which have an x value of 1), we need to adjust the x-axis limits so that they start at a more reasonable position. This can be achieved using plt.xlim() with custom values.

Solution: Adjusting plt.step() and X-Axis Limits

To fix both issues, we’ll update the plt.step() call to exclude zipping (which is not necessary) and adjust the x-axis limits so that they start at a more reasonable position. Here’s the corrected code:

for i, (team, l) in enumerate(df.groupby('Team', sort=False)):
    plt.step(l['Game_week'], l['Position'],
             '-',
             color=colors[team],
             linewidth=8,
             alpha=0.2, zorder=1)

Additionally, we’ll adjust the x-axis limits using plt.xlim():

plt.xlim(0.5, 4.5)  # Start from x = 1 (for alignment with points)
plt.ylim(0.8, 5.2)

Complete Code

Here’s the complete updated code with all corrections and additional explanations:

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

# Data creation
df = pd.DataFrame([['Team1', 1, 1],
                   ['Team1', 2, 2],
                   ['Team1', 1, 3],
                   ['Team1', 5, 4],
                   ['Team1', 1, 5],
                   ['Team2', 2, 1],
                   ['Team2', 3, 2],
                   ['Team2', 4, 3],
                   ['Team2', 4, 4],
                   ['Team2', 3, 5],
                   ['Team3', 3, 1],
                   ['Team3', 4, 2],
                   ['Team3', 3, 3],
                   ['Team3', 2, 4],
                   ['Team3', 2, 5]
                   ], columns=['Team', 'Position', 'Game_week'])

# Data processing
positions = df['Position']
weeks = df['Game_week']
teams = df['Team'].unique()
print(teams)

# Coordinates:
y = positions
x = weeks

fig, ax = plt.subplots()

# Labels:
plt.xlabel('Game weeks')
plt.ylabel('Positions')
plt.xlim(0.5, 4.5)  # Adjusted x-axis limits for alignment with points
plt.ylim(0.8, 5.2)

# Inverting the y-axis:
plt.gca().invert_yaxis()

# x, y ticks:
xi = list(np.unique(x))
yi = list(np.unique(y))
plt.xticks(xi)
plt.yticks(yi)

# Colors for teams:
colors = {'Team1': 'tab:red', 'Team2': 'tab:blue', 'Team3': 'green'}

# Points:
plt.scatter(x, y, s=45, c=df['Team'].map(colors), zorder=2)

# Lines between points:
for i, (team, l) in enumerate(df.groupby('Team', sort=False)):
    plt.step(l['Game_week'], l['Position'],
             '-',
             color=colors[team],
             linewidth=8,
             alpha=0.2, zorder=1)
    print('step:', i, '; team:', [team])
    print(l)

plt.show()
plt.close()

Example Use Case

This updated code can be used to plot lines connecting points for each team according to their tournament position in each game week, ensuring that:

• No additional lines are drawn beyond the actual data
• Lines are aligned with the points (which have an x value of 1)

Last modified on 2024-11-26