Python: Pandas Dataframe how to multiply entire column with a scalar

Question

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)

Doing something like:

df['quantity'] *= -1 # trying to multiply each row's quantity column with -1

gives me a warning:

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:

for idx, row in df.iterrows():
    df.loc[idx, 'quantity'] *= -1

EDIT:

I am running 0.16.2 of Pandas

full trace:

 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

Answer 1

try using apply function.

df['quantity'] = df['quantity'].apply(lambda x: x*-1)

Answer 2

Here's the answer after a bit of research:

df.loc[:,'quantity'] *= -1 #seems to prevent SettingWithCopyWarning 

Answer 3

Note: for those using pandas 0.20.3 and above, and are looking for an answer, all these options will work:

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

   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

Answer 4

More recent pandas versions have the pd.DataFrame.multiply function.

df['quantity'] = df['quantity'].multiply(-1)

Answer 5

A bit old, but I was still getting the same SettingWithCopyWarning. Here was my solution:

df.loc[:, 'quantity'] = df['quantity'] * -1

Answer 6

Try df['quantity'] = df['quantity'] * -1.

Answer 7

I got this warning using Pandas 0.22. You can avoid this by being very explicit using the assign method:

df = df.assign(quantity = df.quantity.mul(-1))

Answer 8

A little late to the game, but for future searchers, this also should work:

df.quantity = df.quantity  * -1

Answer 9

You can use the index of the column you want to apply the multiplication for

df.loc[:,6] *= -1

This will multiply the column with index 6 with -1.