我在PySpark有一只考拉DataFrame。我想要计算逐列的标准差。我试过这样做:
df2['x_std'] = df2[['x_1',
'x_2',
'x_3',
'x_4',
'x_5',
'x_6',
'x_7',
'x_8',
'x_9',
'x_10','x_11',
'x_12']].std(axis = 1) 我得到以下错误:
TypeError: 'DataFrame' object does not support item assignment我还做了一些类似的事情:
d1 = df2[['x_1',
'x_2',
'x_3',
'x_4',
'x_5',
'x_6',
'x_7',
'x_8',
'x_9',
'x_10','x_11',
'x_12']].std(axis = 1)
df2['x_std'] = d1 # d1 is a Koalas Series that should get assigned to the new column.在执行此操作时,我收到以下错误:
Cannot combine column argument because it comes from a different dataframe对考拉来说是全新的。有谁能给点建议吗?谢谢。
发布于 2020-02-15 04:10:25
您可以将选项"compute.ops_on_diff_frames"设置为True,然后执行该操作。
import databricks.koalas as ks
ks.set_option("compute.ops_on_diff_frames", True)
kdf = ks.DataFrame(
{'a': [1, 2, 3, 4, 5, 6],
'b': [2, 1, 7, 4, 2, 3],
'c': [3, 7, 1, 4, 6, 5],
'd': [4, 2, 3, 4, 3, 8],},)
kdf['dev'] = kdf[['a', 'b', 'c', 'd']].std(axis=1)
print (kdf)
a b c d dev
0 1 2 3 4 1.241909
5 6 3 5 8 2.363684
1 2 1 7 2 2.348840
3 4 4 4 4 1.788854
2 3 7 1 3 2.223378
4 5 2 6 3 1.856200不确定它是否为good practice,因为默认情况下是不允许的。
https://stackoverflow.com/questions/58757923
复制相似问题