Python Pandas - n X m DataFrame multiplied by 1 X m Dataframe

问题

I am trying to multiply a 10X7 Pandas dataframe by a 1X7 dataframe in Python.

Here is what I have:

df = pd.DataFrame(np.random.rand(10,7),columns=list('ABCDEFG'))
df_1 = pd.DataFrame(np.random.rand(1,7),columns=list('ABCDEFG'))

I tried this:

df_prod = pd.DataFrame(columns=df)
for i in range(0, df.shape[0]):
    df_prod.iloc[i,:] = df[i,:].tolist()*df_1.iloc[0,:].tolist()

But I get this error message:

Traceback (most recent call last):
  File "C:\Python27\test.py", line 29, in <module>
    df_elem.iloc[i,:] = df_val[i,:].tolist()*df_cf.iloc[0,:].tolist()
  File "C:\python27\lib\site-packages\pandas\core\frame.py", line 1678, in __getitem__
    return self._getitem_column(key)
  File "C:\python27\lib\site-packages\pandas\core\frame.py", line 1685, in _getitem_column
    return self._get_item_cache(key)
  File "C:\python27\lib\site-packages\pandas\core\generic.py", line 1050, in _get_item_cache
    res = cache.get(item)
TypeError: unhashable type

I need to multiply all rows of df by df_1.

I need:

df.iloc[0,:] * df_1
df.iloc[1,:] * df_1
df.iloc[2,:] * df_1
df.iloc[3,:] * df_1
.
.
.
.
df.iloc[9,:] * df_1

Is there a simple way to achieve this multiplication this in Python?

回答1:

If you want to do the multiplication row-wise you could try this:

%timeit df_prod = df.apply(lambda x: x * df_1.ix[0],axis = 1)
100 loops, best of 3: 6.21 ms per loop

however it will be much faster to do the multiplication column-wise:

%timeit = df_prod = pd.DataFrame({c:df[c]* df_1[c].ix[0] for c in df.columns})
100 loops, best of 3: 2.4 ms per loop

回答2:

like this:

%%timeit
df.mul(df_1.ix[0])
1000 loops, best of 3: 251 µs per loop

check results match:

all(df.mul(df_1.ix[0]) == df.apply(lambda x: x * df_1.ix[0],axis = 1))
True

This avoids apply. Link to docs

来源：https://stackoverflow.com/questions/30563934/python-pandas-n-x-m-dataframe-multiplied-by-1-x-m-dataframe