Piyush S. Wanare
Piyush S. Wanare

Reputation: 4933

Pandas how to find position of cell startswith string

I have following data frame I want to find the index for cell which are starts with certain string.

Example :

Price   | Rate p/lot |  Total Comm|
 947.2      1.25        BAM 1.25

 129.3      2.1         NAD 1.25

 161.69     0.8         CAD 2.00

If I have search for ['NAD']:-

Expected output:-

(1,2)

Upvotes: 4

Views: 1768

Answers (3)

Piyush S. Wanare
Piyush S. Wanare

Reputation: 4933

For reference if anyone wants to fetch for position for cell contains substring.

import pandas as pd

df = pd.DataFrame([[947.2, 1.25, 'BAM 1.25'],
                   [129.3, 2.1, '$ 1.25'],
                   [161.69, '0.8 $', 'CAD 2.00']],
                  columns=['Price', 'Rate p/lot', 'Total Comm'])


row, column = (df.applymap(lambda x: x if ('$') in str(x) else None )).values.nonzero()
t = list(zip(row,column))

Upvotes: 0

jpp
jpp

Reputation: 164773

You can do this efficiently with numpy.argwhere:

import pandas as pd, numpy as np

df = pd.DataFrame([[947.2, 1.25, 'BAM 1.25'],
                   [129.3, 2.1, 'NAD 1.25'],
                   [161.69, 0.8, 'CAD 2.00']],
                  columns=['Price', 'Rate p/lot', 'Total Comm'])

res = np.argwhere(df.values.astype('<U3') == 'NAD')

# array([[1, 2]], dtype=int64)

This gives you an array of coordinates where your condition is matched.

To get a single tuple:

res = next(map(tuple, np.argwhere(df.values.astype('<U3') == 'NAD')))

# (1, 2)

For a list of strings:

res = list(map(tuple, np.argwhere(np.logical_or.reduce(\
      [df.values.astype('<U3') == i for i in np.array(['BAM', 'NAD'])]))))

Upvotes: 1

jezrael
jezrael

Reputation: 863226

Use applymap with startswith:

i, j = (df.applymap(lambda x: str(x).startswith('NAD'))).values.nonzero()
t = list(zip(i, j))
print (t)
[(1, 2)]

For list of input values use:

L = ['NAD','BAM']
i, j = (df.applymap(lambda x: str(x).startswith(tuple(L)))).values.nonzero()
t = list(zip(i, j))
print (t)

[(0, 2), (1, 2)]

Upvotes: 1

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