[英]Drop Values from Pandas Dataframe Groups of a Column keeping 1 STD from mean of Groups
on a Pandas df I want to drop rows on a column when its individual value is more or less 1 std from the mean of the group.在 Pandas df 上,当列的单个值与组的平均值相差或多或少 1 个标准时,我想在列上删除行。
For instance, I have a list of names related to an state, and I want to drop every instance that is above or below 1 std of price of the state.例如,我有一个与 state 相关的名称列表,我想删除高于或低于 state 价格标准的每个实例。
thx.谢谢。
#df
state price
a 10
a 30
a 60
b 60
b 50
...
n x
stats = df.groupby('state')['price'].describe()
edit: thanks @MYousefi编辑:谢谢@MYousefi
but look my output, i still can see outliers on the second graph但看看我的 output,我仍然可以在第二张图上看到异常值
Edit2: problem solved with @MYousefi link below Edit2:问题通过下面的@MYousefi 链接解决
One way to do it is to calculate the deviation from the mean and select.一种方法是计算与平均值和 select 的偏差。
df = pd.DataFrame([['a', 10], ['a', 30], ['a', 60], ['b', 10], ['b', 50], ['b', 60]], columns = ['state', 'price'])
agg = df.groupby('state')['price'].agg(['mean', 'std'])
df[((df[['state', 'price']].set_index('state')['price'] - agg['mean']).abs() / agg['std']).reset_index(drop=True) <= 1]
The output of the last statement should be:最后一条语句的 output 应该是:
state price
0 a 10
1 a 30
4 b 50
5 b 60
Also found Pandas filter anomalies per group by Zscore which is the same thing I believe.还发现Pandas 按 Zscore 的每组过滤器异常,这与我相信的相同。
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