如何修改熊猫数据框？
[英]How to modify the pandas dataframe?
问题描述
date_part spot datetimes bad_ticks gap_count bet_duration wins trend std trend_old fakei
1357113602 1357113602 344.25 2013-01-02 1 -9999 60 1 0 -9999 -9999 0
1357113603 1357113602 344.25 2013-01-02 0 -9999 60 1 0 -9999 -9999 1
1357113604 1357113604 348.53 2013-01-02 1 -9999 60 1 0 -9999 -9999 2
This is my simple dataframe which I try to modify using 
这是我尝试使用修改的简单数据框
und_data['trend'][und_data[und_data['fakei']==0].index]
1357113602 2
und_data['trend'][und_data[und_data['fakei']==0].index]=3
This doesn't work. 这行不通。 I checked in Wes Mckinsey Book and my method seems to be correct. 我检查了韦斯·麦肯锡书，我的方法似乎是正确的。 Not sure why it's not working. 不知道为什么它不起作用。 Strangely if I type 奇怪的是我打字
und_data['trend'][und_data[und_data['fakei']==0].index]
It gives the output as 3...but doesn't show in the below output. 它的输出为3 ...但在下面的输出中没有显示。 Something too confusing with copies etc? 复印件太混乱了吗？ Can anyone explain this intuitively. 任何人都可以直观地解释这一点。 These simply things seem way convoluted in pandas. 这些简单的事情似乎在大熊猫中令人费解。
und_data.head()
date_part spot datetimes bad_ticks gap_count bet_duration wins trend std trend_old fakei
1357113602 1357113602 344.25 2013-01-02 1 -9999 60 1 0 -9999 -9999 0
1357113603 1357113602 344.25 2013-01-02 0 -9999 60 1 0 -9999 -9999 1
1357113604 1357113604 348.53 2013-01-02 1 -9999 60 1 0 -9999 -9999 2
1 个解决方案
解决方案1
0 已采纳 2014-10-21 04:16:37
I'm not entirely sure if I'm copying your data in correctly, but I think you want: 我不确定是否要正确复制您的数据，但我认为您需要：
und_data.loc[und_data['fakei'] == 0, 'trend'] = 3
und_data.head()
Out[10]:
date_part spot datetimes bad_ticks gap_count 1357113602 1357113602 344.25 2013-01-02 1 -9999 60
1357113603 1357113602 344.25 2013-01-02 0 -9999 60
1357113604 1357113604 348.53 2013-01-02 1 -9999 60
bet_duration wins trend std trend_old fakei
1357113602 1357113602 1 0 3 -9999 0
1357113603 1357113602 1 0 -9999 -9999 1
1357113604 1357113604 1 0 -9999 -9999 2
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