我有一个数据框,df包含
Index Date & Time eventName eventCount
0 2017-08-09 ABC 24
1 2017-08-09 CDE 140
2 2017-08-10 CDE 150
3 2017-08-11 DEF 200
4 2017-08-11 ABC 20
5 2017-08-16 CDE 10
6 2017-08-16 ABC 15
7 2017-08-17 CDE 10
8 2017-08-17 DEF 50
9 2017-08-18 DEF 80
...
我想为每个每周发生的事件总结一次eventCount,并绘制每周每天(从MON到SUN)的总事件的情节,例如: eventCount值的总和:
2017-08-09 and 2017-08-16(Mondays)=189
2017-08-10 and 2017-08-17(Tuesdays)=210
2017-08-16 and 2017-08-23(Wednesdays)=300
我试过了
dailyOccurenceSum=df['eventCount'].groupby(lambda x: x.weekday).sum()
我收到此错误:AttributeError:'int'对象没有属性'weekday'
答案 0 :(得分:1)
从df
开始 -
df
Index Date & Time eventName eventCount
0 0 2017-08-09 ABC 24
1 1 2017-08-09 CDE 140
2 2 2017-08-10 CDE 150
3 3 2017-08-11 DEF 200
4 4 2017-08-11 ABC 20
5 5 2017-08-16 CDE 10
6 6 2017-08-16 ABC 15
7 7 2017-08-17 CDE 10
8 8 2017-08-17 DEF 50
9 9 2017-08-18 DEF 80
首先,将Date & Time
转换为datetime
列 -
df['Date & Time'] = pd.to_datetime(df['Date & Time'])
接下来,在工作日名称上调用groupby
+ sum
。
df = df.groupby(df['Date & Time'].dt.weekday_name)['eventCount'].sum()
df
Date & Time
Friday 300
Thursday 210
Wednesday 189
Name: eventCount, dtype: int64
如果您想按工作日排序,请将索引转换为分类并调用sort_index
-
cat = ['Monday','Tuesday','Wednesday','Thursday','Friday','Saturday', 'Sunday']
df.index = pd.Categorical(df.index, categories=cat, ordered=True)
df = df.sort_index()
df
Wednesday 189
Thursday 210
Friday 300
Name: eventCount, dtype: int64