In PANDAS, how to get the index of a known value?

Question

If we have a known value in a column, how can we get its index-value? For example:

In [148]: a = pd.DataFrame(np.arange(10).reshape(5,2),columns=[\'c1\',\'c2\'         


        

Answer 1

There might be more than one index map to your value, it make more sense to return a list:

In [48]: a
Out[48]: 
   c1  c2
0   0   1
1   2   3
2   4   5
3   6   7
4   8   9

In [49]: a.c1[a.c1 == 8].index.tolist()
Out[49]: [4]

Answer 2

To get the index by value, simply add .index[0] to the end of a query. This will return the index of the first row of the result...

So, applied to your dataframe:

In [1]: a[a['c2'] == 1].index[0]     In [2]: a[a['c1'] > 7].index[0]   
Out[1]: 0                            Out[2]: 4                         

Where the query returns more than one row, the additional index results can be accessed by specifying the desired index, e.g. .index[n]

In [3]: a[a['c2'] >= 7].index[1]     In [4]: a[(a['c2'] > 1) & (a['c1'] < 8)].index[2]  
Out[3]: 4                            Out[4]: 3 

Answer 3

Using the .loc[] accessor:

In [25]: a.loc[a['c1'] == 8].index[0]
Out[25]: 4

Can also use the get_loc() by setting 'c1' as the index. This will not change the original dataframe.

In [17]: a.set_index('c1').index.get_loc(8)
Out[17]: 4

Answer 4

The other way around using numpy.where() :

import numpy as np
import pandas as pd

In [800]: df = pd.DataFrame(np.arange(10).reshape(5,2),columns=['c1','c2'])

In [801]: df
Out[801]: 
   c1  c2
0   0   1
1   2   3
2   4   5
3   6   7
4   8   9

In [802]: np.where(df["c1"]==6)
Out[802]: (array([3]),)

In [803]: indices = list(np.where(df["c1"]==6)[0])

In [804]: df.iloc[indices]
Out[804]: 
   c1  c2
3   6   7

In [805]: df.iloc[indices].index
Out[805]: Int64Index([3], dtype='int64')

In [806]: df.iloc[indices].index.tolist()
Out[806]: [3]

Answer 5

I think this may help you , both index and columns of the values.

value you are looking for is not duplicated:

poz=matrix[matrix==minv].dropna(axis=1,how='all').dropna(how='all')
value=poz.iloc[0,0]
index=poz.index.item()
column=poz.columns.item()

you can get its index and column

duplicated:

matrix=pd.DataFrame([[1,1],[1,np.NAN]],index=['q','g'],columns=['f','h'])
matrix
Out[83]: 
   f    h
q  1  1.0
g  1  NaN
poz=matrix[matrix==minv].dropna(axis=1,how='all').dropna(how='all')
index=poz.stack().index.tolist()
index
Out[87]: [('q', 'f'), ('q', 'h'), ('g', 'f')]

you will get a list