Python:Plt条形图-不同颜色

在Python中，如何使

'reported'

条变为绿色，使

'UNREPORTED'

条变为红色？ 我想给图表中每个报告的和未报告的条赋予不同的颜色

new = (('AXIN', 37, 'reported'),
     ('LGR', 30, 'UNREPORTED'),
     ('NKD', 24, 'reported'),
     ('TNFRSF', 23, 'reported'),
     ('CCND', 19, 'reported'),
     ('APCDD', 18, 'reported'),
     ('TRD', 16, 'reported'),
     ('TOX', 15, 'UNREPORTED'), 
     ('LEF', 15, 'reported'),
     ('MME', 13, 'reported'))

#sort them as most common gene comes first
new = sorted(new, key=lambda score: score[1], reverse=True) 
#X, Y zip of the tuple new are for plt.bar 
X, Y, _ = zip(*new)    

import seaborn as sns
sns.set()
import matplotlib.pyplot as plt 
%matplotlib inline

plt.figure(figsize = (20, 10))

mytitle = "Most common genes coexpressed with {gene1}, {gene2}, {gene3}, {gene4}".format(
    gene1="Axin2", gene2="Lef", gene3="Nkd1", gene4="Lgr5")
plt.title(mytitle, fontsize=40)

plt.ylabel('Number of same gene encounters across studies', fontsize=20)
ax = plt.bar(range(len(X)), Y, 0.6, tick_label = X, color="green") 
ax = plt.xticks(rotation=90)

new = tuple(new)

---

您可以遍历这些条，检查给定索引的报告是否为“未报告”。如果是这种情况，请使用

set\u color

为条形图着色

---

您需要将颜色列表或元组传递给

plt.bar

，而不仅仅是一种颜色。您可以通过创建颜色字典，然后构建颜色列表来实现

new = sorted(new, key=lambda score: score[1], reverse=True) 
# save the reporting type as R
X, Y, R = zip(*new)    

# create color dictionary
color_dict = {'reported':'green', 'UNREPORTED':'red'}

plt.figure(figsize = (20, 10))
mytitle = "Most common genes coexpressed with {gene1}, {gene2}, {gene3}, {gene4}".format(
    gene1="Axin2", gene2="Lef", gene3="Nkd1", gene4="Lgr5")
plt.title(mytitle, fontsize=40)

plt.ylabel('Number of same gene encounters across studies', fontsize=20)
# build the colors from the color dictionary
ax = plt.bar(range(len(X)), Y, 0.6, tick_label = X, color=[color_dict[r] for r in R])

可能重复的

new = sorted(new, key=lambda score: score[1], reverse=True) 
# save the reporting type as R
X, Y, R = zip(*new)    

# create color dictionary
color_dict = {'reported':'green', 'UNREPORTED':'red'}

plt.figure(figsize = (20, 10))
mytitle = "Most common genes coexpressed with {gene1}, {gene2}, {gene3}, {gene4}".format(
    gene1="Axin2", gene2="Lef", gene3="Nkd1", gene4="Lgr5")
plt.title(mytitle, fontsize=40)

plt.ylabel('Number of same gene encounters across studies', fontsize=20)
# build the colors from the color dictionary
ax = plt.bar(range(len(X)), Y, 0.6, tick_label = X, color=[color_dict[r] for r in R])