Python：Pandas Dataframe 如何将整列与标量相乘
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Python: Pandas Dataframe how to multiply entire column with a scalar
提问by labheshr
How do I multiply each element of a given column of my dataframe with a scalar? (I have tried looking on SO, but cannot seem to find the right solution)
如何将数据帧给定列的每个元素与标量相乘？（我曾尝试寻找 SO，但似乎无法找到正确的解决方案）
Doing something like:
做类似的事情：
df['quantity'] *= -1 # trying to multiply each row's quantity column with -1
gives me a warning:
给我一个警告：
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
Note: If possible, I do not want to be iterating over the dataframe and do something like this...as I think any standard math operation on an entire column should be possible w/o having to write a loop:
注意：如果可能，我不想遍历数据框并执行类似的操作……因为我认为对整个列进行任何标准数学运算都应该是可能的，而不必编写循环：
for idx, row in df.iterrows():
df.loc[idx, 'quantity'] *= -1
EDIT:
编辑：
I am running 0.16.2of Pandas
我在跑0.16.2熊猫
full trace:
完整跟踪：
SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
self.obj[item] = s
采纳答案by labheshr
Here's the answer after a bit of research:
这是经过一番研究后的答案：
df.loc[:,'quantity'] *= -1 #seems to prevent SettingWithCopyWarning
回答by GiannisIordanou
Try df['quantity'] = df['quantity'] * -1.
试试df['quantity'] = df['quantity'] * -1。
回答by maswadkar
try using apply function.
尝试使用应用功能。
df['quantity'] = df['quantity'].apply(lambda x: x*-1)
回答by Rglish
A bit old, but I was still getting the same SettingWithCopyWarning. Here was my solution:
有点旧，但我仍然得到相同的 SettingWithCopyWarning。这是我的解决方案：
df.loc[:, 'quantity'] = df['quantity'] * -1
回答by DJK
Note: for those using pandas 0.20.3 and above, and are looking for an answer, all these options will work:
注意：对于那些使用 Pandas 0.20.3 及更高版本并正在寻找答案的人，所有这些选项都将起作用：
df = pd.DataFrame(np.ones((5,6)),columns=['one','two','three',
'four','five','six'])
df.one *=5
df.two = df.two*5
df.three = df.three.multiply(5)
df['four'] = df['four']*5
df.loc[:, 'five'] *=5
df.iloc[:, 5] = df.iloc[:, 5]*5
which results in
这导致
one two three four five six
0 5.0 5.0 5.0 5.0 5.0 5.0
1 5.0 5.0 5.0 5.0 5.0 5.0
2 5.0 5.0 5.0 5.0 5.0 5.0
3 5.0 5.0 5.0 5.0 5.0 5.0
4 5.0 5.0 5.0 5.0 5.0 5.0
回答by Michael Rice
回答by stephenb
More recent pandas versions have the pd.DataFrame.multiply function.
最近的熊猫版本具有 pd.DataFrame.multiply 功能。
df['quantity'] = df['quantity'].multiply(-1)
回答by Hyman Fleeting
A little late to the game, but for future searchers, this also should work:
游戏有点晚了，但对于未来的搜索者来说，这也应该有效：
df.quantity = df.quantity * -1
回答by DINA TAKLIT
You can use the index of the column you want to apply the multiplication for
您可以使用要应用乘法的列的索引
df.loc[:,6] *= -1
This will multiply the column with index 6 with -1.
这会将索引为 6 的列与 -1 相乘。
回答by Sarah
The real problem of why you are getting the error is not that there is anything wrong with your code: you can use either iloc, loc, or apply, or *=, another of them could have worked.
为什么会出现错误的真正问题不在于您的代码有什么问题：您可以使用iloc, loc, or apply, or *=，其中另一个可以工作。
The real problem that you have is due to how you created the df DataFrame. Most likely you created your df as a slice of another DataFrame without using .copy().The correct way to create your df as a slice of another DataFrame is df = original_df.loc[some slicing].copy().
您遇到的真正问题在于您如何创建 df DataFrame。很可能您将 df 创建为另一个 DataFrame 的一个切片，而没有使用.copy().将 df 创建为另一个 DataFrame 的一个切片的正确方法是df = original_df.loc[some slicing].copy().
The problem is already stated in the error message you got " SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead"
You will get the same message in the most current version of pandas too.
该问题已在您收到的错误消息中说明：“ SettingWithCopyWarning: 正在尝试在 DataFrame 的切片副本上设置值。尝试使用 .loc[row_indexer,col_indexer] = value 代替”
您将收到相同的消息在最新版本的熊猫中也是如此。
Whenever you receive this kind of error message, you should always check how you created your DataFrame. Chances are you forgot the .copy()
每当您收到此类错误消息时，您应该始终检查您创建 DataFrame 的方式。你可能忘记了.copy()
