Reputation: 4933
Example:
Price | Rate p/lot | Total Comm|
947.2 1.25 BAM 1.25
129.3 2.1 $ 1.25
161.69 $ 0.8 CAD 2.00
If I have search for ['$','CAD']:-
Expected output:-
[(1, 2), (2, 1),(2,2)]
Upvotes: 1
Views: 57
Reputation: 1392
Use str.contains
:
df = df.astype(str)
from itertools import product
result = reduce(lambda x,y:x+y, [list(product([i],list(df.iloc[:,i][df.iloc[:,i].str.contains('\$|CAD')].index))) for i in range(len(df.columns))])
Output
[(1, 2), (2, 1), (2, 2)]
Upvotes: 1
Reputation: 863226
You can use in
with applymap
:
i, j = (df.applymap(lambda x: '$' in str(x))).values.nonzero()
t = list(zip(i, j))
print (t)
[(1, 2), (2, 1)]
i, j = (df.applymap(lambda x: any(y for y in L if y in str(x)))).values.nonzero()
#another solution
#i, j = (df.applymap(lambda x: any(s in str(x) for s in L))).values.nonzero()
t = list(zip(i, j))
print (t)
[(1, 2), (2, 1), (2, 2)]
Upvotes: 1
Reputation: 4933
Sorry, find solution like this,It may help someone
import pandas as pd
df = pd.DataFrame([[947.2, 1.25, 'BAM 1.25'],
[129.3, 2.1, '$ 1.25'],
[161.69, '0.8 $', 'CAD 2.00']],
columns=['Price', 'Rate p/lot', 'Total Comm'])
row, column = (df.applymap(lambda x: x if any(s in str(x) for s in ['$','CAD']) else None )).values.nonzero()
t = list(zip(row,column))
Upvotes: 1