Python 访问数据列中的总_秒数()
我想在pandas数据帧中创建一个新列,它是从数据帧开始经过的时间。我正在将日志文件导入到包含数据时间信息的数据帧中,但访问Python 访问数据列中的总_秒数(),python,datetime,pandas,Python,Datetime,Pandas,我想在pandas数据帧中创建一个新列,它是从数据帧开始经过的时间。我正在将日志文件导入到包含数据时间信息的数据帧中,但访问s\u df['delta\u t']中的total\u seconds()函数不起作用。如果我访问列的各个元素(s_df['delta_t'].iloc[8].total_seconds()),它会起作用,但我想创建一个包含total_seconds()的新列,但尝试失败 s_df['t'] = s_df.index # s_df['t] is a column of
s\u df['delta\u t']
中的total\u seconds()
函数不起作用。如果我访问列的各个元素(s_df['delta_t'].iloc[8].total_seconds()
),它会起作用,但我想创建一个包含total_seconds()的新列,但尝试失败
s_df['t'] = s_df.index # s_df['t] is a column of datetime
s_df['delta_t'] = ( s_df['t'] - s_df['t'].iloc[0]) # time since start of data frame
s_df['elapsed_seconds'] = # want column s_df['delta_t'].total_seconds()
使用访问器:
s_df['elapsed_seconds'] = s_df['delta_t'].dt.total_seconds()
例如:
In [82]:
df = pd.DataFrame({'date': pd.date_range(dt.datetime(2010,1,1), dt.datetime(2010,2,1))})
df['delta'] = df['date'] - df['date'].iloc[0]
df
Out[82]:
date delta
0 2010-01-01 0 days
1 2010-01-02 1 days
2 2010-01-03 2 days
3 2010-01-04 3 days
4 2010-01-05 4 days
5 2010-01-06 5 days
6 2010-01-07 6 days
7 2010-01-08 7 days
8 2010-01-09 8 days
9 2010-01-10 9 days
10 2010-01-11 10 days
11 2010-01-12 11 days
12 2010-01-13 12 days
13 2010-01-14 13 days
14 2010-01-15 14 days
15 2010-01-16 15 days
16 2010-01-17 16 days
17 2010-01-18 17 days
18 2010-01-19 18 days
19 2010-01-20 19 days
20 2010-01-21 20 days
21 2010-01-22 21 days
22 2010-01-23 22 days
23 2010-01-24 23 days
24 2010-01-25 24 days
25 2010-01-26 25 days
26 2010-01-27 26 days
27 2010-01-28 27 days
28 2010-01-29 28 days
29 2010-01-30 29 days
30 2010-01-31 30 days
31 2010-02-01 31 days
In [83]:
df['total_seconds'] = df['delta'].dt.total_seconds()
df
Out[83]:
date delta total_seconds
0 2010-01-01 0 days 0
1 2010-01-02 1 days 86400
2 2010-01-03 2 days 172800
3 2010-01-04 3 days 259200
4 2010-01-05 4 days 345600
5 2010-01-06 5 days 432000
6 2010-01-07 6 days 518400
7 2010-01-08 7 days 604800
8 2010-01-09 8 days 691200
9 2010-01-10 9 days 777600
10 2010-01-11 10 days 864000
11 2010-01-12 11 days 950400
12 2010-01-13 12 days 1036800
13 2010-01-14 13 days 1123200
14 2010-01-15 14 days 1209600
15 2010-01-16 15 days 1296000
16 2010-01-17 16 days 1382400
17 2010-01-18 17 days 1468800
18 2010-01-19 18 days 1555200
19 2010-01-20 19 days 1641600
20 2010-01-21 20 days 1728000
21 2010-01-22 21 days 1814400
22 2010-01-23 22 days 1900800
23 2010-01-24 23 days 1987200
24 2010-01-25 24 days 2073600
25 2010-01-26 25 days 2160000
26 2010-01-27 26 days 2246400
27 2010-01-28 27 days 2332800
28 2010-01-29 28 days 2419200
29 2010-01-30 29 days 2505600
30 2010-01-31 30 days 2592000
31 2010-02-01 31 days 2678400