英文:
Assign different color to each plt.step line
问题
我已经让它工作了，只有两个问题：
-
由于每次绘制线条时都为每个队伍进行迭代，因此会绘制第4条（紫色）线条，尽管只有3支队伍。这条线是为每次迭代（每支队伍）绘制的。但为什么呢？
-
线条是从x = 0的起点绘制的，因此与点（已正确绘制）不对齐。线条应该从x = 1的起点开始绘制，根据它们的Game_week值。
输出：
我错过了什么？
以下是示例代码：
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
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'])
positions = df['Position']
weeks = df['Game_week']
teams = df['Team'].unique()
print(teams)
# 坐标:
y = positions
x = weeks
print(y)
print(x)
fig, ax = plt.subplots()
# 标签:
plt.xlabel('Game weeks')
plt.ylabel('Positions')
plt.xlim(-0.2, 5.2)
plt.ylim(0.8, 5.2)
# 反转y轴:
plt.gca().invert_yaxis()
# x, y刻度:
xi = list(np.unique(x))
yi = list(np.unique(y))
plt.xticks(xi)
plt.yticks(yi)
# 队伍的颜色:
colors = {'Team1': 'tab:red', 'Team2': 'tab:blue', 'Team3': 'blue'}
# 点:
plt.scatter(x, y, s=45, c=df['Team'].map(colors), zorder=2)
# 点之间的线:
for i, (team, l) in enumerate(df.groupby('Team', sort=False)):
plt.step(list(zip(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()
谢谢！
英文:
I have a code which draws lines for the teams according to their tournament position in each game week.
Pretty much I managed to make it work, except 2 things:
- For some reason a 4th (violet) line is drawn (teams are only 3) which goes from the top to the bottom throughout each game week. As I found out this line is drawn for every iteration (for each team) when plotting the lines. But why?
- Lines are drawn from x = 0 starting point, thus not aligning with the points (which are drawn correctly). Lines should be drawn from x = 1 starting point as well (according to their Game_week value).
Output:
What have I missed?
Example of the code:
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
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'])
positions = df['Position']
weeks = df['Game_week']
teams = df['Team'].unique()
print(teams)
# Coordinates:
y = positions
x = weeks
print(y)
print(x)
fig, ax = plt.subplots()
# Labels:
plt.xlabel('Game weeks')
plt.ylabel('Positions')
plt.xlim(-0.2, 5.2)
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': 'blue'}
# 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(list(zip(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()
Thank you!
答案1
得分: 2
问题出在plt.step()，你正在使用zip。根据文档这里，你只需要提供x和y的值。将该行更新如下...
for i, (team, l) in enumerate(df.groupby('Team', sort=False)):
plt.step(l['Game_week'], l['Position'], ## 不需要zip
'-',
color=colors[team],
linewidth=8,
alpha=0.2, zorder=1)
...将给你这个图。是否满足你的需求？你可能想要更改xlim，也许从0.8开始。
英文:
The issues is with the plt.step(), where you are using zip. As per documentation here, you just need to give the x and y values. Updating that line as below...
for i, (team, l) in enumerate(df.groupby('Team', sort=False)):
plt.step(l['Game_week'], l['Position'], ## No zip
'-',
color=colors[team],
linewidth=8,
alpha=0.2, zorder=1)
.. will give you this plot. Does this meet your needs? You may want to change xlim to start at 0.8 perhaps.
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