python - 在 pandas 中查找一列中的共同值与另一列中的不同值

Question

我有一个像这样的数据框

event    cust
 et1   satya
 et1    papu
 et1     abc
 et1   satya
 et1     def
 et2    papu
 et2   satya
 et2   panda
 et3  normal
 et3   panda
 et3   satya
 et3     fgh

现在我需要找出所有 3 种类型的事件都存在的“cust”。所以这应该会产生

event  cust
et1  satya
et1  satya

不用担心不同(可以删除重复项)。为此我的方法是

x  = df[df['event'] == 'et1']
y  = df[df['event'] == 'et2']
z  = df[df['event'] == 'et3']
df_common = x[x['cust'].isin(y[y['cust'].isin(z.cust)]['cust'])]

但这在这种情况下是不合适的，因为 DataFrame 大小很大，我必须为 50-100 多个事件找到共同的客户。

请建议一些 pandas/more-pythonic 方法来做到这一点。提前致谢。

Answer 1

你可以尝试:

#first drop duplicates in each group by event
df = df.drop_duplicates(['event','cust'])

#count  values
counts = df.cust.value_counts()
print counts
satya     3
panda     2
papu      2
def       1
normal    1
fgh       1
abc       1
Name: cust, dtype: int64

#get number of unique events
uniqevents = df.event.nunique()
print uniqevents
3
#get values with count == uniqevents
counts = counts[counts == uniqevents]
print counts
satya    3
Name: cust, dtype: int64

print counts.index.to_series().reset_index(drop=True)
0    satya
dtype: object