及時繪制pandas數據框

Question

我有一個數據框，白天包含應用程序中的錯誤：

 date code server type 2017-06-20 ADFC-64001 nexteesadf_server1 WARNING 2017-06-20 ADFC-64001 nexteesadf_server1 WARNING 2017-06-20 ADFC-64003 nexteesadf_server1 WARNING 2017-06-20 ADFC-64003 nexteesadf_server1 WARNING 2017-06-20 ADFC-64002 nexteesadf_server1 WARNING 2017-06-20 ADFC-64001 nexteesadf_server1 WARNING 2017-06-20 ADFC-64003 nexteesadf_server1 WARNING 2017-06-20 ADFC-64003 nexteesadf_server1 WARNING 2017-06-20 ADFC-64002 nexteesadf_server1 WARNING 2017-06-20 ADFC-64001 nexteesadf_server1 WARNING 

我現在想把每天每個錯誤的＃次出現作為折線圖及時繪制。 因此，ADFC-64001將有1行，ADFC-64002將有1行等等。

做這個的最好方式是什么？

提前致謝。

Answer 1

df['date'] = pd.to_datetime(df['date'])
df = df.set_index('date')
print(df.groupby('code').resample('D').count().type.unstack('date').fillna(0))

date        2017-06-20  2017-06-21  2017-06-22  2017-06-23  2017-06-25
code                                                                  
ADFC-64001         4.0         1.0         0.0         0.0         1.0
ADFC-64002         2.0         0.0         0.0         1.0         0.0
ADFC-64003         3.0         2.0         1.0         0.0         0.0

數據

          date        code              server     type
0   2017-06-20  ADFC-64001  nexteesadf_server1  WARNING
1   2017-06-20  ADFC-64001  nexteesadf_server1  WARNING
2   2017-06-20  ADFC-64003  nexteesadf_server1  WARNING
3   2017-06-20  ADFC-64003  nexteesadf_server1  WARNING
4   2017-06-20  ADFC-64002  nexteesadf_server1  WARNING
5   2017-06-20  ADFC-64001  nexteesadf_server1  WARNING
6   2017-06-20  ADFC-64003  nexteesadf_server1  WARNING
7   2017-06-21  ADFC-64003  nexteesadf_server1  WARNING
8   2017-06-20  ADFC-64002  nexteesadf_server1  WARNING
9   2017-06-20  ADFC-64001  nexteesadf_server1  WARNING
10  2017-06-21  ADFC-64001  nexteesadf_server1  WARNING
11  2017-06-21  ADFC-64003  nexteesadf_server1  WARNING
12  2017-06-22  ADFC-64003  nexteesadf_server1  WARNING
13  2017-06-23  ADFC-64002  nexteesadf_server1  WARNING
14  2017-06-25  ADFC-64001  nexteesadf_server1  WARNING

情節

import matplotlib.pyplot as plt

plt.style.use('ggplot')
df.groupby('code').resample('D').count().type.unstack('date').fillna(0).T.plot()
plt.show()