如何避免 colors 在 matplotlib 中的两个 plot 类型之间混淆

Question

我有以下结果：

这是一个plt.scatter有plt.bar的。

出于某种原因，条形图被着色，但我希望它具有特定颜色，它不属于散点图 plot 使用的 colors 的一部分。 我该如何做到这一点？

我当前的代码：

from collections import OrderedDict
import matplotlib.pyplot as plt
from matplotlib.pyplot import figure

def scatter_plot_from_to_delta(start, end, title="Delta times per day"):
  filtered = OrderedDict()

  # Generating filrered score dict (K=participant, V=list of each day's delta, with 0 as filtered out) 
  for name in names:
    score = list()
    for delta in scores.get(name):
      if delta > end or delta < start:
        delta = 0
      score.append(delta)
    filtered[name] = score

  figure(figsize=(20, 11)) # size of the whole graph

  # Preparing data for listed participants
  listed = OrderedDict() # (K=name displayed in the graph, V=amount of times displayed)
  latest_listed_day = 1 # ends up determining the last X axis value in the graph
  for key, value in filtered.items():
    listed[key] = dict()
    listed[key]['amnt'] = 0
    x = list()
    y = list()
    for i, val in enumerate(value):
      if val != 0:
        x.append(i+1)
        latest_listed_day = max(i+1, latest_listed_day)
        y.append(val)
        listed[key]['amnt'] += 1
    if listed[key]['amnt'] == 0:
      del listed[key]
    else:
      listed[key]['x'] = x
      listed[key]['y'] = y
  ordered_counter = OrderedDict(sorted(listed.items(), reverse=True, key=lambda item: item[1]['amnt']))
  print(ordered_counter)

  # Scatter plot
  for key, value in ordered_counter.items():
    x = value['x']
    y = value['y']
    plt.scatter(x, y, s=200) # s=size of the dots
    for i, _ in enumerate(x):
      plt.annotate(key, (x[i]+0.15, y[i]-0.27)) # marking names by each dot

  # Bar chart for the amount of listed participants on each day
  for i in range(num_challenges-1):
    participants_listed_that_day = 0
    for _, val in filtered.items():
      s = val[i]
      if s != 0:
        participants_listed_that_day += 1
    if participants_listed_that_day != 0:
      plt.bar(i+1, participants_listed_that_day)
      # Displaying the total per day above each bar
      plt.text(i+0.908,
              participants_listed_that_day+0.15,
              str(participants_listed_that_day),
              fontsize=18)

  # Concatenate (sorted) amount of times displayed for more info in legend
  displayed = list()
  for key, value in ordered_counter.items():
    concat = "(" + str(value['amnt']) + ") " + key
    displayed.append(concat)

  # Legend of listed participants
  plt.legend(displayed,
             scatterpoints=11,
             loc='center left',
             bbox_to_anchor=(1, 0.5),
             ncol=1,
             fontsize=16)

  plt.xticks(range(1,latest_listed_day+1)) # ensure x axis tick for every day
  plt.xlim((0.5,latest_listed_day+1.5)) # force displayed x range

  plt.title(title, fontsize=30)
  plt.xlabel("Day")
  plt.ylabel("Delta (in seconds)")
  plt.show()

Answer 1

You can choose two discrete or qualitative colormaps that have distinct colors from each other (and also enough colors to exceed the number of categories in your data), such as tab10 and tab20b , then update the scatter plot and bar chart portions of your function.

import matplotlib.cm as cm

# Scatter plot
for key, value in ordered_counter.items():
  x = value['x']
  y = value['y']

  plt.scatter(x, y, s=200, cmap=cm.tab10) # s=size of the dots
  for i, _ in enumerate(x):
    plt.annotate(key, (x[i]+0.15, y[i]-0.27)) # marking names by each dot

# Bar chart for the amount of listed participants on each day
for i in range(num_challenges-1):
  participants_listed_that_day = 0
  for _, val in filtered.items():
    s = val[i]
    if s != 0:
      participants_listed_that_day += 1
  if participants_listed_that_day != 0:
    plt.bar(i+1, participants_listed_that_day, color=cm.tab20b)
    # Displaying the total per day above each bar
    plt.text(i+0.908,
            participants_listed_that_day+0.15,
            str(participants_listed_that_day),
            fontsize=18)