Select rows in dataFrame with the same index using python

Question

I want to ask you, How to select rows that have the same index number in a DataFrame. Example:

df=

  A, B, C,
0 1. 2. 1.
1 2. 2. 2. 
2 2. 2. 2. 
3 3. 3. 4.
  A, B, C,
0 1. 2. 1.
1 2. 2. 2. 
2 2. 2. 0. 
3 3. 3. 4.
  A, B, C,
0 1. 2. 1.
1 2. 2. 2. 
2 0. 2. 2. 
3 3. 3. 4.

I expect:

df1=

   A, B, C,
 2 2. 2. 2. 
 2 2. 2. 0. 
 2 0. 2. 2.

I'm using df.loc[2] but only shows me the first set of data. Also used df1=df.set_index(['2']) and doesn't works too. Thanks in advance!

Is wear, my df.index= Out[101]: RangeIndex(start=0, stop=874, step=1) but I can see index of variable length [1,2,3,4,5,,1,2,3,,1,2,3...] and the output of my columns is: Index(['Unnamed: 0', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34' — Jonathan Pacheco
– Jonathan Pacheco, Commented May 12, 2017 at 23:31
Can you paste sample input and sample output and the code , what attempts you have made so far at solving the problem? — Satyadev
– Satyadev, Commented May 12, 2017 at 23:58

Karmugilan JAYACHANDIRAN · Accepted Answer · 2019-06-10 11:58:08Z

2

The index may have duplicates. Especially, when you concatenate different data frames. Use this to filter data based on your index:

df1 = df[df.index==2]

answered Jun 10, 2019 at 11:58

Karmugilan JAYACHANDIRAN

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Comments

DYZ · Accepted Answer · 2017-05-13 01:25:19Z

1

Looks like you need to group by the index values:

df1 = df.groupby(df.index).get_group(2)
df1
#   A  B  C
#2  2  2  2
#2  2  2  0
#2  0  2  2

answered May 13, 2017 at 1:25

DYZ

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2 Comments

Jonathan Pacheco Over a year ago

does not work for me! with that I only get the first

DYZ Over a year ago

Please update the original question to include the correct definition of df (they way it is typed now, it is not a valid Pandas dataframe; I assumed that it had 12 rows, three columns A, B, and C, and a repeated index).

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