如何按类别随时间变化绘制图表

Question

我有两列，分类列和年份列，我正在尝试绘制它们。我试图将每年每个类别的总和来创建一个多类时间序列图。

ax = data[data.categorical=="cat1"]["categorical"].plot(label='cat1')
data[data.categorical=="cat2"]["categorical"].plot(ax=ax, label='cat3')
data[data.categorical=="cat3"]["categorical"].plot(ax=ax, label='cat3')
plt.xlabel("Year")
plt.ylabel("Number per category")
sns.despine()

但出现错误，指出没有要绘制的数字数据。我正在寻找与上面类似的东西，也许与data[data.categorical=="cat3"]["categorical"].lambda x : (1 for x in data.categorical)

我将使用以下列表作为示例。

categorical = ["cat1","cat1","cat2","cat3","cat2","cat1","cat3","cat2","cat1","cat3","cat3","cat3","cat2","cat1","cat2","cat3","cat2","cat2","cat3","cat1","cat1","cat1","cat3"]

year = [2013,2014,2013,2015,2014,2014,2013,2014,2014,2015,2015,2013,2014,2014,2013,2014,2015,2015,2015,2013,2014,2015,2013]

我的目标是获得类似于下图的东西

Answer 1

我不太愿意称其为“解决方案”，因为它基本上只是 Pandas 基本功能的摘要，在您在帖子中找到时间序列图的同一文档中对此进行了解释。但鉴于周围groupby和情节上存在一些混乱，演示可能有助于澄清问题。

我们可以使用两次调用groupby().
第一个groupby()使用聚合获取每年类别出现的计数count。
第二个groupby()用于绘制每个类别的时间序列。

首先，生成一个示例数据框：

import pandas as pd
categorical = ["cat1","cat1","cat2","cat3","cat2","cat1","cat3","cat2",
               "cat1","cat3","cat3","cat3","cat2","cat1","cat2","cat3",
               "cat2","cat2","cat3","cat1","cat1","cat1","cat3"]
year = [2013,2014,2013,2015,2014,2014,2013,2014,2014,2015,2015,2013,
        2014,2014,2013,2014,2015,2015,2015,2013,2014,2015,2013]
df = pd.DataFrame({'categorical':categorical,
                   'year':year})

   categorical  year
 0        cat1  2013
 1        cat1  2014
                 ...
21        cat1  2015
22        cat3  2013

现在获取每年每个类别的计数：

# reset_index() gives a column for counting, after groupby uses year and category
ctdf = (df.reset_index()
          .groupby(['year','categorical'], as_index=False)
          .count()
          # rename isn't strictly necessary here, it's just for readability
          .rename(columns={'index':'ct'})
       )

   year categorical  ct
0  2013        cat1   2
1  2013        cat2   2
2  2013        cat3   3
3  2014        cat1   5
4  2014        cat2   3
5  2014        cat3   1
6  2015        cat1   1
7  2015        cat2   2
8  2015        cat3   4

最后，绘制每个类别的时间序列，按颜色键控：

from matplotlib import pyplot as plt
fig, ax = plt.subplots()

# key gives the group name (i.e. category), data gives the actual values
for key, data in ctdf.groupby('categorical'):
    data.plot(x='year', y='ct', ax=ax, label=key)