Python 熊猫：如何根据频率有效过滤数据

我有一个包含三列的数据框，follower、user和ratio

对于u中的每个唯一元素，我想知道它发生了多少次，并删除与出现次数少于5次的元素对应的行。这是我的代码，效率很低。我想知道如何正确地书写它

known_follower_id= np.unique(following_df.follower.values) # IDs of members of the list in the saved database
userid, counts = np.unique(following_df.user.values, return_counts= True) # ID of people they followed in the saved database
count_idx=np.argsort(-counts) # number of times a user was followed
trimmed_following_df= following_df.copy(deep= True)

th = 5
idx_th = counts< th

userid_removed = userid[idx_th]
idx_userid_rem= [i for i,v in enumerate(trimmed_following_df.user.values) if v in userid_removed]

trimmed_following_df=trimmed_following_df.drop(idx_userid_rem)

known_follower_id=np.unique（跟随_df.follower.values）#已保存数据库中列表成员的id
userid，counts=np.unique（遵循_df.user.values，返回_counts=True）#他们在保存的数据库中跟踪的人的ID
count_idx=np.argsort（-counts）#跟踪用户的次数
修剪后的\u following\u df=following\u df.copy（deep=True）
th=5
idx_th=计数

以下是我将如何替代数据。看看这是否能帮你得到你想要的

import pandas as pd
df = pd.DataFrame({
    'follower': ['John', 'Jane', 'Jack', 'Suzy', 'Kate', 'Mark', 'Alex', 'Boby', 'Cris', 'Duke'],
    'user':     ['milk', 'milk', 'milk', 'milk', 'milk', 'milk', 'pear', 'pear', 'wire', 'silk'],
    'ratio':    [.4, .4, .5, .2, .6, .3, .5, .8, .9, .2]})
print (df)

df['usercount'] = df['user'].map(df['user'].value_counts())

df = df[df['usercount'] > 5]
df.drop(columns=['usercount'],inplace=True)
print (df)

其输出将为：

原始数据帧：

  follower  user  ratio
0     John  milk    0.4
1     Jane  milk    0.4
2     Jack  milk    0.5
3     Suzy  milk    0.2
4     Kate  milk    0.6
5     Mark  milk    0.3
6     Alex  pear    0.5
7     Boby  pear    0.8
8     Cris  wire    0.9
9     Duke  silk    0.2

  follower  user  ratio
0     John  milk    0.4
1     Jane  milk    0.4
2     Jack  milk    0.5
3     Suzy  milk    0.2
4     Kate  milk    0.6
5     Mark  milk    0.3

更新的数据帧：

  follower  user  ratio
0     John  milk    0.4
1     Jane  milk    0.4
2     Jack  milk    0.5
3     Suzy  milk    0.2
4     Kate  milk    0.6
5     Mark  milk    0.3
6     Alex  pear    0.5
7     Boby  pear    0.8
8     Cris  wire    0.9
9     Duke  silk    0.2

  follower  user  ratio
0     John  milk    0.4
1     Jane  milk    0.4
2     Jack  milk    0.5
3     Suzy  milk    0.2
4     Kate  milk    0.6
5     Mark  milk    0.3

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请您发布一个示例数据集和所需的输出。我想我明白了这个问题，但我想确定输出是否符合要求。