Question

我有一个python数据帧（df1），它有一个列时间。我使用pd.to_datetime(df1['time'])将列转换为日期时间序列。现在我得到一个这样的列：

2016-08-24 00:00:00  2016-08-13  00:00:00   
2016-08-24 00:00:00  2016-08-13  00:00:00     
2016-08-24 00:00:00  2016-08-13  00:00:00   
2016-08-24 00:00:00  2016-08-13  00:00:00  
2016-08-24 00:00:01  2016-08-13  00:00:01   
2016-08-24 00:00:01  2016-08-13  00:00:01   
2016-08-24 00:00:02  2016-08-13  00:00:02  
2016-08-24 00:00:02  2016-08-13  00:00:02     
2016-08-24 00:00:02  2016-08-13  00:00:02    
2016-08-24 00:00:02  2016-08-13  00:00:02     
2016-08-24 00:00:02  2016-08-13  00:00:02     
2016-08-24 00:00:02  2016-08-13  00:00:02     
2016-08-24 00:00:02  2016-08-13  00:00:02    
2016-08-24 00:00:02  2016-08-13  00:00:02    
2016-08-24 00:00:02  2016-08-13  00:00:02     
....

2016-08-24 23:59:59  2016-08-13  00:00:02

基本上，我希望第一列按小时分组，以便我可以在1小时内看到有多少条目。任何帮助都会很棒。

Answer 1

使用@jezrael设置。

df.resample(rule='H', how='count').rename(columns = {'time':'count'})

                      count
2016-08-24 00:00:00      1
2016-08-24 01:00:00      3
2016-08-24 02:00:00      1

Answer 2

使用resample：

#pandas version 0.18.0 and higher
df = df.resample('H').size()

#pandas version below 0.18.0
#df = df.resample('H', 'size')

print (df)
2016-08-24 00:00:00    1
2016-08-24 01:00:00    3
2016-08-24 02:00:00    1
Freq: H, dtype: int64

如果需要输出DataFrame：

df = df.resample('H').size().rename('count').to_frame()
print (df)
                     count
2016-08-24 00:00:00      1
2016-08-24 01:00:00      3
2016-08-24 02:00:00      1

或者您可以转换为DatetimeIndex然后汇总size，从minutes seconds和<M8[h]中移除：

import pandas as pd

df = pd.DataFrame({'time': {pd.Timestamp('2016-08-24 01:00:00'): pd.Timestamp('2016-08-13 00:00:00'), pd.Timestamp('2016-08-24 01:00:01'): pd.Timestamp('2016-08-13 00:00:01'), pd.Timestamp('2016-08-24 01:00:02'): pd.Timestamp('2016-08-13 00:00:02'), pd.Timestamp('2016-08-24 02:00:02'): pd.Timestamp('2016-08-13 00:00:02'), pd.Timestamp('2016-08-24 00:00:00'): pd.Timestamp('2016-08-13 00:00:00')}})
print (df)
                                   time
2016-08-24 00:00:00 2016-08-13 00:00:00
2016-08-24 01:00:00 2016-08-13 00:00:00
2016-08-24 01:00:01 2016-08-13 00:00:01
2016-08-24 01:00:02 2016-08-13 00:00:02
2016-08-24 02:00:02 2016-08-13 00:00:02

df= df.groupby([df.index.values.astype('<M8[h]')]).size()
print (df)
2016-08-24 00:00:00    1
2016-08-24 01:00:00    3
2016-08-24 02:00:00    1
dtype: int64

Answer 3

您可以按如下方式使用if((err = netconn_recv(conn, &inbuf)) == ERR_OK) { netbuf_first(inbuf); do{ netbuf_data(inbuf, (void**)&buf, &buflen); //recieve_buffer=concat(recieve_buffer,buf); DBGSTR("%d",i); i++; }while(netbuf_next(inbuf) >= 0); }。

pandas.DatetimeIndex

[参考文献] Python Pandas: Group datetime column into hour and minute aggregations

使用Python，如何按小时对Dataframe中的列进行分组？

3 个答案: