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']) In [149]: a Out[149]: c1 c2 0 0 1 1 2 3 2 4 5 ........ As we know, we can get a value by the index corresponding to it, like this.
In [151]: a.ix[0,1] In [152]: a.c2[0] In [154]: a.c2.ix[0] <-- use index Out[151]: 1 Out[152]: 1 Out[154]: 1 <-- get value But how to get the index by value?
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] 
a.c1[a.c1 == 8].index.tolist()[0]
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 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] 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 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
