Find All Indices/instances Of All Repeating Patterns Across Columns And Rows Of Pandas Dataframe

Suppose I have a simple pandas dataframe df as so: | name | car | |----|-----------|-------| | 0 | 'bob' | 'b' | | 1 | 'bob' | 'c' | | 2 | 'fox' | 'b

Solution 1:

Use boolean indexing with Series.isin instead second and third conditions:

df1 = df[(df.name == 'bob') & df.car.isin(['b','c'])]
print (df1)
   name car
0   bob   b
1   bob   c
8   bob   b
9   bob   c
10  bob   b
11  bob   c

If need index values:

out_idx = df.index[(df.name == 'bob') & df.car.isin(['b','c'])]

Or:

out_idx = df[(df.name == 'bob') & df.car.isin(['b','c'])].index

Your solution is possible with | (bitwise OR) instead second & and also added one ():

df1 = df[(df.name == 'bob') & ((df.car == 'b') | (df.car == 'c'))]