pandas select column by index code example

Example 1: pandas select column by index

#    A  B  C
# 0  1  3  5
# 1  2  4  6

column_B = a_dataframe.iloc[:, 1]
print(column_B)

# OUTPUT
# 0    3
# 1    4

Example 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)

Example 3: select columns pandas

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

Example 4: loc and iloc in pandas

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

Example 5: retrieve row by index pandas

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

Example 6: loc and iloc in pandas

iloc slicing gives all the data upto the position that is passed as argument
loc gives all the data upto the label that is passed as argument
n = pd.Series([1,2,3,4],index = [0,1,2,3])
print("With iloc we got")
print(n.iloc[:2])
print("With loc we got")
print(n.loc[:2])

<Output>
With iloc we got
0    1
1    2
dtype: int64
With loc we got
0    1
1    2
2    3
dtype: int64