Python Subset pandas dataframe based on first n unique elements from a column-CodePudding

I have a pandas dataframe (df) with many subjects.

 #   Column                Non-Null Count  Dtype  
---  ------                --------------  -----  
 0   subject               20640 non-null  object 

 1   block                 20640 non-null  int64

Say I want to subset the df with the first n unique subjects (keeping all rows for those n subjects). Is there an easy command to do that?

CodePudding user response：

Use boolean indexing with filter first unique values with Series.isin:

n = 10
df1 = df[df['subject'].isin(df['subject'].unique()[:n])]

Or:

df1 = df[df['subject'].isin(df['subject'].drop_duplicates().head(n))]

If need first unique consecutive values:

print (df)
  subject
0       a
1       a
2       b
3       f
4       d
5       g
6       a <-should be removed
7       b <-should be removed

n= 3
s = df['subject'].ne(df['subject'].shift()).cumsum()
print (s)
0    1
1    1
2    2
3    3
4    4
5    5
6    6
7    7
Name: subject, dtype: int32

df1 = df[s.le(n)]
print (df1)
  subject
0       a
1       a
2       b
3       f