我有一个Pandas系列,基于一个随机数,我想选择一行(下面的代码示例中为5)并删除该行.删除行时,我想为剩余的行(0到8)创建一个新索引.代码如下:
print 'Original series: ', sample_mean_series
print 'Length of original series', len(sample_mean_series)
sample_mean_series = sample_mean_series.drop([5],axis=0)
print 'Series with item 5 dropped: ', sample_mean_series
print 'Length of modified series:', len(sample_mean_series)
print sample_mean_series.reindex(range(len(sample_mean_series)))
这是输出:
Original series:
0 0.000074
1 -0.000067
2 0.000076
3 -0.000017
4 -0.000038
5 -0.000051
6 0.000125
7 -0.000108
8 -0.000009
9 -0.000052
Length of original series 10
Series with item 5 dropped:
0 0.000074
1 -0.000067
2 0.000076
3 -0.000017
4 -0.000038
6 0.000125
7 -0.000108
8 -0.000009 …我有几个时间序列合并到一个常见的DataFrame的问题.我正在使用的示例代码:
import pandas
import datetime
import numpy as np
start = datetime.datetime(2001, 1, 1)
end = datetime.datetime(2001, 1, 10)
dates = pandas.date_range(start, end)
serie_1 = pandas.Series(np.random.randn(10), index = dates)
start = datetime.datetime(2001, 1, 2)
end = datetime.datetime(2001, 1, 11)
dates = pandas.date_range(start, end)
serie_2 = pandas.Series(np.random.randn(10), index = dates)
start = datetime.datetime(2001, 1, 3)
end = datetime.datetime(2001, 1, 12)
dates = pandas.date_range(start, end)
serie_3 = pandas.Series(np.random.randn(10), index = dates)
print 'serie_1'
print serie_1
print 'serie_2'
print serie_2
print 'serie_3'
print …我有一个带有整数索引的pandas系列,我已按其排序(按值),我如何按系列中的位置访问值.
例如:
s_original = pd.Series({0: -0.000213, 1: 0.00031399999999999999, 2: -0.00024899999999999998, 3: -2.6999999999999999e-05, 4: 0.000122})
s_sorted = np.sort(s_original)
In [3]: s_original
Out[3]:
0 -0.000213
1 0.000314
2 -0.000249
3 -0.000027
4 0.000122
In [4]: s_sorted
Out[4]:
2 -0.000249
0 -0.000213
3 -0.000027
4 0.000122
1 0.000314
In [5]: s_sorted[3]
Out[5]: -2.6999999999999999e-05
但我想得到值0.000122即位置 3 的项目.
我该怎么做？
我希望能够根据数据框中的部分数据计算滚动标准差。一个例子将解释我想要完成的任务。
A B C
2000-01-01 0.425615 1.679789 -1.903056
2000-01-02 0.791313 0.562471 0.098124
2000-01-03 1.223165 -0.548387 -1.558204
2000-01-04 0.354931 -0.685773 0.647817
2000-01-05 1.137434 1.000594 0.428180
2000-01-06 -0.265311 -1.807045 0.533477
2000-01-07 0.717505 1.647540 -0.141123
2000-01-08 -2.405664 1.278410 1.043872
2000-01-09 0.463943 0.982042 -0.382241
2000-01-10 -0.403267 -0.615421 0.583384
2000-01-11 -0.714163 0.470505 -0.291396
2000-01-12 0.209979 -0.118331 -0.369776
2000-01-13 -0.779638 0.924612 -0.477497
2000-01-14 0.149868 -0.376292 0.747637
2000-01-15 -0.464360 0.821400 1.412874
这就是我希望能够做到的：