Problem
Let’s say I have the Pandas dataframe below:
df = DataFrame({'A' : [5,6,3,4], 'B' : [1,2,3, 5]})
df
A B
0 5 1
1 6 2
2 3 3
3 4 5
I have the ability to subset depending on a specified value:
x = df[df['A'] == 3]
x
A B
2 3 3
How, on the other hand, can I subset based on a list of values? – anything along these lines:
list_of_values = [3,6]
y = df[df['A'] in list_of_values]
To get:
A B
1 6 2
2 3 3
Asked by zach
Solution #1
The isin technique can be used:
In [1]: df = pd.DataFrame({'A': [5,6,3,4], 'B': [1,2,3,5]})
In [2]: df
Out[2]:
A B
0 5 1
1 6 2
2 3 3
3 4 5
In [3]: df[df['A'].isin([3, 6])]
Out[3]:
A B
1 6 2
2 3 3
And here’s how to use it the other way around:
In [4]: df[~df['A'].isin([3, 6])]
Out[4]:
A B
0 5 1
3 4 5
Answered by Wouter Overmeire
Solution #2
You can use the query method:
df.query('A in [6, 3]')
# df.query('A == [6, 3]')
or
lst = [6, 3]
df.query('A in @lst')
# df.query('A == @lst')
Answered by Mykola Zotko
Solution #3
Another method;
df.loc[df.apply(lambda x: x.A in [3,6], axis=1)]
This method, unlike the isin method, is especially useful for determining whether the list contains a function of column A. As an example, consider the function f(A) = 2*A – 5;
df.loc[df.apply(lambda x: 2*x.A-5 in [3,6], axis=1)]
This method is slower than the isin method, so keep that in mind.
Answered by Achintha Ihalage
Post is based on https://stackoverflow.com/questions/12096252/use-a-list-of-values-to-select-rows-from-a-pandas-dataframe