<p>IIUC您可以跳过<code>df_source</code>列<code>A</code>的第一行,方法是选择所有行而不首先选择<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.ix.html" rel="nofollow">^{<cd3>}</a>:</p>
<pre><code>df_target["A"].ix[1:] = df_source['A'].ix[1:] + 1
print df_target
A
0 1000.000000
1 0.988898
2 0.986142
3 1.009979
4 1.005165
5 1.101116
6 0.992312
7 0.962890
8 1.051340
9 1.009750
</code></pre>
<p>或者你认为:</p>
<pre><code>import pandas as pd
import numpy as np
df_source = pd.DataFrame(np.random.normal(0,.05,10), index=range(10), columns=['A'])
print df_source
A
0 0.039965
1 0.060821
2 -0.079238
3 -0.129932
4 0.002196
5 -0.003721
6 -0.008358
7 0.014104
8 -0.022905
9 0.014793
df_target = pd.DataFrame(index = df_source.index)
#all A set to 1000
df_target["A"] = 1000 # initialize target array to start at 1000
print df_target
A
0 1000
1 1000
2 1000
3 1000
4 1000
5 1000
6 1000
7 1000
8 1000
9 1000
</code></pre>
<pre><code>df_target["A"] = (1 + df_source["A"].shift(-1))* df_target["A"]
print df_target
A
0 1060.820882
1 920.761946
2 870.067878
3 1002.195555
4 996.279287
5 991.641909
6 1014.104402
7 977.094961
8 1014.793488
9 NaN
</code></pre>
<p>编辑:</p>
<p>也许你需要<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.cumsum.html" rel="nofollow">^{<cd4>}</a>:</p>
<pre><code>df_target["B"] = 2
df_target["C"] = df_target["B"].cumsum()
df_target["D"] = df_target["B"] + df_target.index
print df_target
A B C D
0 1041.003000 2 2 2
1 1013.817000 2 4 3
2 948.853000 2 6 4
3 1031.692000 2 8 5
4 970.875000 2 10 6
5 1011.095000 2 12 7
6 1053.472000 2 14 8
7 903.765000 2 16 9
8 1010.546000 2 18 10
9 0.010546 2 20 11
</code></pre>