select DF columns python
df = df.iloc[:,0:2]
df = df[['column1', 'column2']]
select DF columns python
df = df.iloc[:,0:2]
df = df[['column1', 'column2']]
how to pick out separate columns from the pandas dataframe object
df1 = df.iloc[:, 0:2] # If you want to do it by index. Remember that Python does not slice inclusive of the ending index.
df1 = df[['a', 'b']] ## if you want to do it b nae
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)
select columns pandas
df1 = df.iloc[:,0:2] # Remember that Python does not slice inclusive of the ending index.
Select a Column in pandas data Frame notation
df.favorite food
select columns in pandas df
In [8]: age_sex = titanic[["Age", "Sex"]]
In [9]: age_sex.head()
Out[9]:
Age Sex
0 22.0 male
1 38.0 female
2 26.0 female
3 35.0 female
4 35.0 male
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