使用熊猫堆叠条形图

我想以条形图的形式表示我的数据，如我的预期输出所示。

time,date,category
0,2002-05-01,2
1,2002-05-02,0
2,2002-05-03,0
3,2002-05-04,0
4,2002-05-05,0
5,2002-05-06,0
6,2002-05-07,0
7,2002-05-08,2
8,2002-05-09,2
9,2002-05-10,0
10,2002-05-11,2
11,2002-05-12,0
12,2002-05-13,0
13,2002-05-14,2
14,2002-05-15,2
15,2002-05-16,2
16,2002-05-17,2
17,2002-05-18,2
18,2002-05-19,0
19,2002-05-20,0
20,2002-05-21,1
21,2002-05-22,2
22,2002-05-23,0
23,2002-05-24,1
24,2002-05-25,0
25,2002-05-26,0
26,2002-05-27,0
27,2002-05-28,0
28,2002-05-29,1
29,2002-05-30,0

import pandas as pd
from datetime import datetime
import matplotlib.pyplot as plt

df = pd.read_csv('df.csv')
daily_category = df[['date','category']]
daily_category['weekday'] = pd.to_datetime(daily_category['date']).dt.day_name()
daily_category_plot = daily_category[['weekday','category']]

daily_category_plot[['category']].groupby('weekday').count().plot(kind='bar', legend=None)
plt.show()

但是，我收到以下错误

回溯（最后一次调用）：文件“day_plot.py”，第 10 行，在 daily_category_plot[['category']].groupby('weekday').count().plot(kind='bar', legend=None ) 文件“/home/..../.local/lib/python3.6/site-packages/pandas/core/frame.py”，第 6525 行，在 groupby dropna=dropna，文件“/home/... ./.local/lib/python3.6/site-packages/pandas/core/groupby/groupby.py”，第 533 行，在init dropna=self.dropna，文件“/home/..../.local/ lib/python3.6/site-packages/pandas/core/groupby/grouper.py"，第 786 行，在 get_grouper 中引发 KeyError(gpr) KeyError: 'weekday'

********** 下面的另一个示例，我在下面手动提取数据返回几乎预期的输出，除了日期表示为数字而不是工作日名称。***********

Day,category1,category2,category3
Sunday,0,0,4
Monday,0,0,4
Tuesday,1,1,2
Wednesday,1,4,0
Thursday,0,2,3
Friday,1,1,2
Saturday,0,2,2

import pandas as pd 
import numpy as np 
import matplotlib.pyplot as plt

df = pd.read_csv('df.csv')

ax = df.plot.bar(stacked=True, color=['green', 'red', 'blue'])
ax.set_xticklabels(labels=df.index, rotation=70, rotation_mode="anchor", ha="right")
ax.set_xlabel('')
ax.set_ylabel('Number of days')
plt.show()

测试输出

更新的代码产生奇怪的情节

import pandas as pd
from datetime import datetime
import matplotlib.pyplot as plt

df = pd.read_csv('df.csv')
daily_category = df[['time','date','category']]
daily_category['weekday'] = pd.to_datetime(daily_category['date']).dt.day_name()

ans = (daily_category.groupby(['weekday', 'category']) 
         .size()
         .reset_index(name='sum')
         .pivot(index='weekday', columns='category', values='sum')
      )

ans.plot.bar(stacked=True)
plt.show()

更新的输出