How to select rows in Pandas dataframe where value appears more than once

Question

Let's say I have the Pandas dataframe with columns of different measurement attributes and corresponding measurement values.

ID     Parameter     Value
0      'A'           4.3
1      'B'           3.1
2      'C'           8.9
3      'A'           2.1
4      'A'           3.9
.      .             .
.      .             .
.      .             .
100    'B'           3.8

How can I filter this dataframe to only have measurements that appear more than X number of times? For example, for this dataframe I want to get all rows with more than 5 measurements (lets say only parameters 'A' and 'B' appear more than 5 times) to get a dataframe like below.

ID     Parameter     Value
0      'A'           4.3
1      'B'           3.1
3      'A'           2.1
.      .             .
.      .             .
.      .             .
100    'B'           3.8

Answer 1

You can use value_counts + isin -

v = df.Parameter.value_counts()
df[df.Parameter.isin(v.index[v.gt(5)])]

---

For example, where K = 2 (get all items which have more than 2 readings) -

df

   ID Parameter  Value
0   0         A    4.3
1   1         B    3.1
2   2         C    8.9
3   3         A    2.1
4   4         A    3.9
5   5         B    4.5

v = df.Parameter.value_counts()
v

A    3
B    2
C    1
Name: Parameter, dtype: int64

df[df.Parameter.isin(v.index[v.gt(2)])]

   ID Parameter  Value
0   0         A    4.3
3   3         A    2.1
4   4         A    3.9

Answer 2

使用带有boolean indexing transform + size ：

df[df.groupby('Parameter')['Parameter'].transform('size') > 5]

Answer 3

通过使用filter

df.groupby('Parameter').filter(lambda x : x['Parameter'].shape[0]>=5)

Answer 4

带计数的Loc也可以工作

df.loc[df.Parameter.isin((df.groupby('Parameter').size().Value >= 5).index)]

Answer 5

You can use value_counts() to get the rows in a DataFrame with their original indexes where the values in for a particular column appear more than once with Series manipulation

more_than_1 = DF['col1'].value_counts()
more_than_1 = list(more_than_1[more_than_1>1].index)
more_than_1_rows = DF[DF['col1'].isin(more_than_1)
more_than_1_rows