Python 使用 pandas groupby 计算唯一值
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Count unique values using pandas groupby
提问by user1684046
I have data of the following form:
我有以下形式的数据：
df = pd.DataFrame({
'group': [1, 1, 2, 3, 3, 3, 4],
'param': ['a', 'a', 'b', np.nan, 'a', 'a', np.nan]
})
print(df)
# group param
# 0 1 a
# 1 1 a
# 2 2 b
# 3 3 NaN
# 4 3 a
# 5 3 a
# 6 4 NaN
Non-null values within groups are always the same. I want to count the non-null value for each group (where it exists) once, and then find the total counts for each value.
组内的非空值始终相同。我想为每个组（它存在的地方）计算一次非空值，然后找到每个值的总计数。
I'm currently doing this in the following (clunky and inefficient) way:
我目前正在以以下（笨拙且低效的）方式执行此操作：
param = []
for _, group in df[df.param.notnull()].groupby('group'):
param.append(group.param.unique()[0])
print(pd.DataFrame({'param': param}).param.value_counts())
# a 2
# b 1
I'm sure there's a way to do this more cleanly and without using a loop, but I just can't seem to work it out. Any help would be much appreciated.
我确信有一种方法可以更干净地做到这一点并且不使用循环，但我似乎无法解决这个问题。任何帮助将非常感激。
回答by jezrael
I think you can use SeriesGroupBy.nunique:
我认为你可以使用SeriesGroupBy.nunique：
print (df.groupby('param')['group'].nunique())
param
a 2
b 1
Name: group, dtype: int64
Another solution with unique, then create new dfby DataFrame.from_records, reshape to Seriesby stackand last value_counts:
另一个解决方案unique，然后创建新的dfby DataFrame.from_records，重塑为Seriesbystack和 last value_counts：
a = df[df.param.notnull()].groupby('group')['param'].unique()
print (pd.DataFrame.from_records(a.values.tolist()).stack().value_counts())
a 2
b 1
dtype: int64
回答by datapug
This is just an add-on to the solution in case you want to compute not only unique values but other aggregate functions:
这只是解决方案的一个附加组件，以防您不仅要计算唯一值，还要计算其他聚合函数：
df.groupby(['group']).agg(['min','max','count','nunique'])
Hope you find it useful
希望你觉得它有用
回答by nir
I know it has been a while since this was posted, but I think this will help too. I wanted to count unique values and filter the groups by number of these unique values, this is how I did it:
我知道这篇文章发布已经有一段时间了，但我认为这也会有所帮助。我想计算唯一值并按这些唯一值的数量过滤组，我是这样做的：
df.groupby('group').agg(['min','max','count','nunique']).reset_index(drop=False)
