python - 曲线末尾的标签 (matplotlib-seaborn)

Question

这个问题已经有答案了:

How to annotate end of lines using python and matplotlib? (3 个回答)

已关闭 4 年前。

我有多个这种格式的数据框:

year    count   cum_sum
2001    5   5
2002    15  20
2003    14  34
2004    21  55
2005    44  99
2006    37  136
2007    55  191
2008    69  260
2009    133 393
2010    94  487
2011    133 620
2012    141 761
2013    206 967
2014    243 1210
2015    336 1546
2016    278 1824
2017    285 2109
2018    178 2287

我生成了如下图: enter image description here

以下代码已用于此目的:

fig, ax = plt.subplots(figsize=(12,8))

sns.pointplot(x="year", y="cum_sum", data=china_papers_by_year_sorted, color='red')
sns.pointplot(x="year", y="cum_sum", data=usa_papers_by_year_sorted, color='blue')
sns.pointplot(x="year", y="cum_sum", data=korea_papers_by_year_sorted, color='lightblue')
sns.pointplot(x="year", y="cum_sum", data=japan_papers_by_year_sorted, color='yellow')
sns.pointplot(x="year", y="cum_sum", data=brazil_papers_by_year_sorted, color='green')

ax.set_ylim([0,2000])
ax.set_ylabel("Cumulative frequency")

fig.text(x = 0.91, y = 0.76, s = "China", color = "red", weight = "bold") #Here I have had to indicate manually x and y coordinates
fig.text(x = 0.91, y = 0.72, s = "South Korea", color = "lightblue", weight = "bold") #Here I have had to indicate manually x and y coordinates

plt.show()

问题在于向绘图添加文本的方法无法识别数据坐标。因此，我必须手动指示每个数据框标签的坐标(请参阅“中国”和“韩国”)。有聪明的方法吗？我看过一个使用“.last_valid_index()”方法的示例。但是，由于无法识别数据坐标，因此它不起作用。

Answer 1

您无需重复调用pointplot并手动添加标签。相反，在数据框中添加一个国家/地区列来指示国家/地区，组合数据框，然后使用国家/地区作为色调简单地绘制累积总和与年份的关系。

相反，请执行以下操作:

# Add a country label to dataframe itself
china_papers_by_year_sorted['country'] = 'China'
usa_papers_by_year_sorted['country'] = 'USA'
korea_papers_by_year_sorted['country'] = 'Korea'
japan_papers_by_year_sorted['country'] = 'Japan'
brazil_papers_by_year_sorted['country'] = 'Brazil'

# List of dataframes with same columns
frames = [china_papers_by_year_sorted, usa_papers_by_year_sorted,
          korea_papers_by_year_sorted, japan_papers_by_year_sorted,
          brazil_papers_by_year_sorted]

# Combine into one dataframe
result = pd.concat(frames)

# Plot.. hue will make country name a label
ax = sns.pointplot(x="year", y="cum_sum", hue="country", data=result)
ax.set_ylim([0,2000])
ax.set_ylabel("Cumulative frequency")
plt.show()

编辑:编辑添加，如果您想注释行本身而不是使用图例，则 this existing question 的答案指示如何注释行尾。