Question

我有一个数据框，我计划用它来构建直方图。

数据框包含以下值。

   starttime hour  
1  7/01/2015    0 
2  7/01/2015    0   
3  7/01/2015    3  
4  7/01/2015    3 
5  7/01/2015    12

我希望得到结果数据框。

   starttime hour     frequency
1  7/01/2015    0             2
2  7/01/2015    3             2
3  7/01/2015    12            1

到目前为止我做了什么

df_values = Df[['starttime','hour']]
values = df_values.groupby(['starttime'])
grouped = values.aggregate(np.sum)

输出我正在

                                                        hour
starttime                                                   
6/01/2015  0000000000000000000000000000000000000000000000...
6/02/2015  0000000000000000000000000000000000000000000000...
6/03/2015  0000000000000000000000000000000000000000000000...
6/04/2015                                                NaN
6/05/2015                                             435211

非常感谢任何帮助。感谢。

Answer 1

使用groupby + size / count -

c = df.columns.tolist() # c = ['starttime', 'hour']
df.groupby(c).size().reset_index(name='frequency')

或者，

df.groupby(c).hour.count().reset_index(name='frequency')

   starttime  hour  frequency
0  7/01/2015     0          2
1  7/01/2015     3          2
2  7/01/2015    12          1

Answer 2

df['freq'] = 1 df.groupby(['starttime','hour', as_index=False]).count()

Pandas数据帧与频率

2 个答案: