CODEWITHSUNDEEP
pythonpandas
drotsky
drotsky

Reputation: 11

How do you get a list of indexes with certain criteria in a dataframe?

For example, I have a Dataframe with non-negative values throughout, but the missing values have been encoded as negative. I want to get all those indexes.

Upvotes: 0

Views: 437

Answers (2)

jpp
jpp

Reputation: 164653

You can calculate the row-wise minimum and check if it is less than 0:

res = df.index[df.min(1) < 0]

# data from @jezrael    
# Int64Index([0, 1, 3, 5], dtype='int64')

Upvotes: 1

jezrael
jezrael

Reputation: 862601

Use boolean indexing with df.index:

df = pd.DataFrame({
         'B':[-4,5,4,5,5,-4],
         'C':[7,8,9,4,2,3],
         'D':[1,3,5,-7,1,0],
         'E':[5,-3,6,9,2,4],

})

print (df)
   B  C  D  E
0 -4  7  1  5
1  5  8  3 -3
2  4  9  5  6
3  5  4 -7  9
4  5  2  1  2
5 -4  3  0  4

idx = df.index[df.lt(0).any(axis=1)]
print (idx)
Int64Index([0, 1, 3, 5], dtype='int64')

Explanation:

First compare all values by DataFrame.lt (<):

(similar functions are gt, le, ge, ne, eq)

print (df.lt(0))
       B      C      D      E
0   True  False  False  False
1  False  False  False   True
2  False  False  False  False
3  False  False   True  False
4  False  False  False  False
5   True  False  False  False

And then check at least one True value per row by DataFrame.any:

print (df.lt(0).any(axis=1))
0     True
1     True
2    False
3     True
4    False
5     True
dtype: bool

Upvotes: 1

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