pandas select column by index

1#    A  B  C
2# 0  1  3  5
3# 1  2  4  6
4
5column_B = a_dataframe.iloc[:, 1]
6print(column_B)
7
8# OUTPUT
9# 0    3
10# 1    4

1from pandas import DataFrame
2
3boxes = {'Color': ['Green','Green','Green','Blue','Blue','Red','Red','Red'],
4         'Shape': ['Rectangle','Rectangle','Square','Rectangle','Square','Square','Square','Rectangle'],
5         'Price': [10,15,5,5,10,15,15,5]
6        }
7
8df = DataFrame(boxes, columns= ['Color','Shape','Price'])
9
10select_color = df.loc[df['Color'] == 'Green']
11print (select_color)
12

1df1 = df.iloc[:,0:2] # Remember that Python does not slice inclusive of the ending index.

1iloc - default indexes (system generated)
2loc - table indexes or we manually given indexes 

1rowData = dfObj.loc[ 'b' , : ]
2

1df = df.loc[df.index.repeat(df['a'])]   
2df['c'] = df.groupby(level=0).cumcount() + 1
3df = df.reset_index(drop=True)
4print (df)
5   a  b  c
60  1  x  1
71  2  y  1
82  2  y  2
93  3  z  1
104  3  z  2
115  3  z  3
12