Python，将id-date相同但值不同的行合并到一列中

Question

我已经选择了提及和未提及"Korona"的行，并按日期对它们进行了计数。有些日期没有Korona True。数据帧看起来像：

表1

计数错误[/tr>37181错误[/tr>错误

	Published_date	Korona
242	2020-06-01	13
243	2020-06-01	真
244	2020-06-02	错误
245	2020-06-02	真
246	2020-06-03	错误	11
247	2020-06-04	错误
248	2020-06-04	真
249	2020-06-05	错误	10
250	2020-06-06	5
251	2020-06-07	5
252	2020-06-08	错误	14

尝试使用数据透视表

d = ''' Published_date  Korona  Count
242 2020-06-01  False   13
243 2020-06-01  True    3
244 2020-06-02  False   7
245 2020-06-02  True    1
246 2020-06-03  False   11
247 2020-06-04  False   8
248 2020-06-04  True    1
249 2020-06-05  False   10
250 2020-06-06  False   5
251 2020-06-07  False   5
252 2020-06-08  False   14'''
df = pd.read_csv(io.StringIO(d), sep='s+', engine='python')
# pivot the data and reset the index
df1 = pd.pivot_table(df, values='Count', index=['Published_date'],
columns=['Korona'], aggfunc=np.sum, fill_value=0).reset_index()
# rename the columns to what you want
df1.columns = ['Published_date', 'Count-NoKorona', 'Count-Korona']
# sum the values into a new column
df1['Count-All'] = df1[['Count-NoKorona', 'Count-Korona']].sum(axis=1)

输出：

Published_date  Count-NoKorona  Count-Korona  Count-All
0     2020-06-01              13             3         16
1     2020-06-02               7             1          8
2     2020-06-03              11             0         11
3     2020-06-04               8             1          9
4     2020-06-05              10             0         10
5     2020-06-06               5             0          5
6     2020-06-07               5             0          5
7     2020-06-08              14             0         14