CODEWITHSUNDEEP
pythonpandas
Kemeia
Kemeia

Reputation: 866

Pandas - find index of value anywhere in DataFrame

I'm new to Python & Pandas.

I want to find the index of a certain value (let's say security_id) in my pandas dataframe, because that is where the columns start. (There is an unknown number of rows with irrelevant data above the columns, as well as a number of empty 'columns' on the left side.)

As far as I see, the isin method only returns a boolean on whether the value exists, not its index.

How do I find the index of this value?

Upvotes: 14

Views: 54232

Answers (6)

tasos
tasos

Reputation: 1

Function finds the positions of a value in a dataframe 

import pandas as pd
import numpy as np

def pandasFindPositionsInDataframe(dfIn,findme):
    positions = []
    irow =0
    while ( irow < len(dfIn.index)):
        list_colPositions=dfIn.columns[dfIn.iloc[irow,:]==findme].tolist()   
        if list_colPositions != []:
            colu_iloc = dfIn.columns.get_loc(list_colPositions[0])
            positions.append([irow, colu_iloc])
        irow +=1

    return positions

Upvotes: 0

Ravishankar Sivasubramaniam
Ravishankar Sivasubramaniam

Reputation: 791

Get the index for rows matching search term in all columns

search = 'security_id' 
df.loc[df.isin([search]).any(axis=1)].index.tolist()

Rows filtered for matching search term in all columns

search = 'search term' 
df.loc[df.isin([search]).any(axis=1)]

Upvotes: 19

Peterd
Peterd

Reputation: 31

A oneliner solution avoiding explicit loops...

  • returning the entire row(s)

    df.iloc[np.flatnonzero((df=='security_id').values)//df.shape[1],:]

  • returning row(s) and column(s)

    df.iloc[ np.flatnonzero((df=='security_id').values)//df.shape[1], np.unique(np.flatnonzero((df=='security_id').values)%df.shape[1]) ]

Upvotes: 3

Jay
Jay

Reputation: 834

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

Upvotes: 3

Adam Slack
Adam Slack

Reputation: 528

I think this question may have been asked before here. The accepted answer is pretty comprehensive and should help you find the index of a value in a column.

Edit: if the column that the value exists in is not known, then you could use:

for col in df.columns:
    df[df[col] == 'security_id'].index.tolist()

Upvotes: 2

Ujjwal
Ujjwal

Reputation: 1859

Supposing that your DataFrame looks like the following :

      0       1            2      3    4
0     a      er          tfr    sdf   34
1    rt     tyh          fgd    thy  rer
2     1       2            3      4    5
3     6       7            8      9   10
4   dsf     wew  security_id   name  age
5   dfs    bgbf          121  jason   34
6  dddp    gpot         5754   mike   37
7  fpoo  werwrw          342   jack   31

Do the following :

for row in range(df.shape[0]): # df is the DataFrame
         for col in range(df.shape[1]):
             if df.get_value(row,col) == 'security_id':
                 print(row, col)
                 break

Upvotes: 2

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