Check if a value exists in pandas dataframe index

Question

I am sure there is an obvious way to do this but cant think of anything slick right now.

Basically instead of raising exception I would like to get True or False to see if a value exists in pandas df index.

import pandas as pd
df = pd.DataFrame({'test':[1,2,3,4]}, index=['a','b','c','d'])
df.loc['g']  # (should give False)

What I have working now is the following

sum(df.index == 'g')

Asked By: Abhi

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Source

Answer 1

This should do the trick

'g' in df.index

Answered By: Guillaume Jacquenot

Answer 2

Just for reference as it was something I was looking for, you can test for presence within the values or the index by appending the “.values” method, e.g.

g in df.<your selected field>.values
g in df.index.values

I find that adding the “.values” to get a simple list or ndarray out makes exist or “in” checks run more smoothly with the other python tools. Just thought I’d toss that out there for people.

Answered By: Ezekiel Kruglick

Answer 3

df = pandas.DataFrame({'g':[1]}, index=['isStop'])

#df.loc['g']

if 'g' in df.index:
    print("find g")

if 'isStop' in df.index:
    print("find a")

Answered By: Gank

Answer 4

Multi index works a little different from single index. Here are some methods for multi-indexed dataframe.

df = pd.DataFrame({'col1': ['a', 'b','c', 'd'], 'col2': ['X','X','Y', 'Y'], 'col3': [1, 2, 3, 4]}, columns=['col1', 'col2', 'col3'])
df = df.set_index(['col1', 'col2'])

in df.index works for the first level only when checking single index value.

'a' in df.index     # True
'X' in df.index     # False

Check df.index.levels for other levels.

'a' in df.index.levels[0] # True
'X' in df.index.levels[1] # True

Check in df.index for an index combination tuple.

('a', 'X') in df.index  # True
('a', 'Y') in df.index  # False

Answered By: broccoli2000

Answer 5

with DataFrame: df_data

>>> df_data
  id   name  value
0  a  ampha      1
1  b   beta      2
2  c     ce      3

I tried:

>>> getattr(df_data, 'value').isin([1]).any()
True
>>> getattr(df_data, 'value').isin(['1']).any()
True

but:

>>> 1 in getattr(df_data, 'value')
True
>>> '1' in getattr(df_data, 'value')
False

So fun 😀

Answered By: Sihc

Answer 6

Code below does not print boolean, but allows for dataframe subsetting by index… I understand this is likely not the most efficient way to solve the problem, but I (1) like the way this reads and (2) you can easily subset where df1 index exists in df2:

df3 = df1[df1.index.isin(df2.index)]

or where df1 index does not exist in df2…

df3 = df1[~df1.index.isin(df2.index)]

Answered By: xxyjoel

Answer 7

I like to use:

if 'value' in df.index.get_level_values(0):
    print(True)

get_level_values method is good because it allows you to get the value in the indexes no matter if your index is simple or composite.

Use 0 (zero) if you have a single index in your dataframe [or you want to check the first index in multiple index levels]. Use 1 for the second index, and so on…

Answered By: Samuel Corradi

Check if a value exists in pandas dataframe index

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