isolate row based on index pandas
dfObj.iloc[: , [0, 2]]isolate row based on index pandas
dfObj.iloc[: , [0, 2]]select rows from dataframe pandas
from pandas import DataFrame
boxes = {'Color': ['Green','Green','Green','Blue','Blue','Red','Red','Red'],
'Shape': ['Rectangle','Rectangle','Square','Rectangle','Square','Square','Square','Rectangle'],
'Price': [10,15,5,5,10,15,15,5]
}
df = DataFrame(boxes, columns= ['Color','Shape','Price'])
select_color = df.loc[df['Color'] == 'Green']
print (select_color)iloc in dataframe
df=pd.read_csv('yourcsv.csv')
X=df.iloc[:,:-1].values
y=df.iloc[:,1].valueshow to use loc and iloc in pandas
>>> df.iloc[0, 1]
2return df.iloc[1:]
>>> df.iloc[1:3, 0:3]
a b c
1 100 200 300
2 1000 2000 3000iloc pandas
Purely integer-location based indexing for selection by position.
.iloc[] is primarily integer position based (from 0 to length-1 of the axis), but may also be used with a boolean array.Copyright © 2021 Codeinu
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