按 pandas 数据框和平均数组中的列分组 [英] Group by column in pandas dataframe and average arrays
问题描述
我有一个电影数据帧，其中包含电影名称，它们各自的流派和矢量表示(numpy数组).
I have a movie dataframe with movie names, their respective genre, and vector representation (numpy arrays).
ID Year Title Genre Word Vector
1 2003.0 Dinosaur Planet Documentary [-0.55423898, -0.72544044, 0.33189204, -0.1720...
2 2004.0 Isle of Man TT 2004 Review Sports & Fitness [-0.373265237, -1.07549703, -0.469254494, -0.4...
3 1997.0 Character Foreign [-1.57682264, -0.91265768, 2.43038678, -0.2114...
4 1994.0 Paula Abdul's Get Up & Dance Sports & Fitness [0.3096168, -0.57186663, 0.39008939, 0.2868615...
5 2004.0 The Rise and Fall of ECW Sports & Fitness [0.17175879, -2.38005066, -0.45771399, 1.32608...
我想按流派分组，以获取每种流派的平均矢量表示(流派中每个电影矢量的分量平均).
I'd like to group by genre and get each genre's average vector representation (the component wise average of each movie vector in the genre).
我第一次尝试:
movie_df.groupby(['Genre']).mean()
但是内置的均值函数无法获取numpy数组的均值.
But the built in mean function isn't able to take the mean of numpy arrays.
我尝试创建自己的函数，然后将其应用于每个组，但是我不确定这是否正确使用了Apply:
I tried creating my own function to do so and then apply it to each group, but I'm not sure this is using apply correctly:
def vector_average(group):
series_to_array = np.array(group.tolist())
return np.mean(series_to_array, axis = 0)
movie_df.groupby(['Genre']).apply(vector_average)
任何指针将不胜感激！
Any pointers would be appreciated!
推荐答案
如果我正确理解，要获取按组件划分的平均值，您可以简单地将np.mean显式应用于'Word Vector' SeriesGroupBy.
If I understand correctly, to get the component-wise averages you can simply apply np.mean to the 'Word Vector' SeriesGroupBy explicitly.
df.groupby('Genre')['Word Vector'].apply(np.mean)
演示
>>> df = pd.DataFrame({'Title': list('ABCDEFGHIJ'),
'Genre': list('ABCBBDCDED'),
'Word Vector': [np.random.randint(0, 10, 10)
for _ in range(len('ABCDEFGHIJ'))]})
>>> df
Genre Title Word Vector
0 A A [3, 6, 8, 0, 4, 8, 1, 4, 0, 1]
1 B B [5, 4, 4, 4, 8, 7, 4, 3, 7, 2]
2 C C [1, 7, 6, 7, 3, 3, 8, 1, 8, 1]
3 B D [0, 4, 6, 7, 1, 5, 5, 0, 6, 7]
4 B E [8, 2, 1, 4, 1, 2, 0, 4, 9, 1]
5 D F [7, 9, 7, 8, 8, 7, 2, 9, 1, 3]
6 C G [0, 7, 1, 9, 6, 2, 1, 0, 3, 7]
7 D H [4, 7, 9, 4, 1, 5, 0, 3, 0, 6]
8 E I [5, 1, 5, 1, 8, 1, 1, 4, 5, 6]
9 D J [7, 9, 0, 1, 8, 3, 8, 8, 1, 0]
>>> df.groupby('Genre')['Word Vector'].apply(np.mean)
Genre
A [3.0, 6.0, 8.0, 0.0, 4.0, 8.0, 1.0, 4.0, 0.0, ...
B [4.33333333333, 3.33333333333, 3.66666666667, ...
C [0.5, 7.0, 3.5, 8.0, 4.5, 2.5, 4.5, 0.5, 5.5, ...
D [6.0, 8.33333333333, 5.33333333333, 4.33333333...
E [5.0, 1.0, 5.0, 1.0, 8.0, 1.0, 1.0, 4.0, 5.0, ...
Name: Word Vector, dtype: object
这篇关于按 pandas 数据框和平均数组中的列分组的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
