Pandas Adding - Deleting columns and Index Operations

Pandas Adding - Deleting columns and Index Operations. The following shows how to add column, delete column from pandas DataFrame and various index Operations using pandas module.

 

In [1]:

import pandas as pd

 

In [2]:

data_list = [0,1,2,3,4,5,6,7,8,9]

data_frame = pd.DataFrame(data_list)
data_frame

Out[2]:

	0
0	0
1	1
2	2
3	3
4	4
5	5
6	6
7	7
8	8
9	9

 

 

Change the name of the column:

In [3]:

data_frame.columns = ['rev']
data_frame

Out[3]:

	rev
0	0
1	1
2	2
3	3
4	4
5	5
6	6
7	7
8	8
9	9

 

Add a column:

In [4]:

data_frame['new_col'] = 5
data_frame

Out[4]:

	rev	new_col
0	0	5
1	1	5
2	2	5
3	3	5
4	4	5
5	5	5
6	6	5
7	7	5
8	8	5
9	9	5

 

Modify our new column:

In [5]:

data_frame['new_col'] = data_frame['new_col'] + 1
data_frame

Out[5]:

	rev	new_col
0	0	6
1	1	6
2	2	6
3	3	6
4	4	6
5	5	6
6	6	6
7	7	6
8	8	6
9	9	6

 

In [6]:

del data_frame['new_col']
data_frame

Out[6]:

	rev
0	0
1	1
2	2
3	3
4	4
5	5
6	6
7	7
8	8
9	9

 

Adding couple of columns:

In [7]:

data_frame['test_col'] = 3
data_frame['another_col'] = data_frame['rev']
data_frame

Out[7]:

	rev	test_col	another_col
0	0	3	0
1	1	3	1
2	2	3	2
3	3	3	3
4	4	3	4
5	5	3	5
6	6	3	6
7	7	3	7
8	8	3	8
9	9	3	9

 

Change the name of the index:

In [8]:

index = ['a','b','c','d','e','f','g','h','i','j']
data_frame.index = index
data_frame

Out[8]:

	rev	test_col	another_col
a	0	3	0
b	1	3	1
c	2	3	2
d	3	3	3
e	4	3	4
f	5	3	5
g	6	3	6
h	7	3	7
i	8	3	8
j	9	3	9

 

Select pieces of the dataframe using loc:

In [9]:

data_frame.loc['a']

Out[9]:

rev            0
test_col       3
another_col    0
Name: a, dtype: int64

 

In [10]:

data_frame.loc['a':'d']

Out[10]:

	rev	test_col	another_col
a	0	3	0
b	1	3	1
c	2	3	2
d	3	3	3

 

In [11]:

data_frame.iloc[0:4]

Out[11]:

	rev	test_col	another_col
a	0	3	0
b	1	3	1
c	2	3	2
d	3	3	3

 

Select using the column name:

In [12]:

data_frame['rev']

Out[12]:

a    0
b    1
c    2
d    3
e    4
f    5
g    6
h    7
i    8
j    9
Name: rev, dtype: int64

 

In [13]:

data_frame[['rev', 'test_col']]

Out[13]:

	rev	test_col
a	0	3
b	1	3
c	2	3
d	3	3
e	4	3
f	5	3
g	6	3
h	7	3
i	8	3
j	9	3

 

In [14]:

data_frame.loc[data_frame.index[0:3], 'rev']

Out[14]:

a    0
b    1
c    2
Name: rev, dtype: int64

 

In [15]:

data_frame.loc[data_frame.index[0:3], ['rev', 'test_col']]

Out[15]:

	rev	test_col
a	0	3
b	1	3
c	2	3

 

In [16]:

data_frame.loc[data_frame.index[5:],'another_col']

Out[16]:

f    5
g    6
h    7
i    8
j    9
Name: another_col, dtype: int64

 

In [17]:

data_frame.loc[data_frame.index[:3],['another_col', 'test_col']]

Out[17]:

	another_col	test_col
a	0	3
b	1	3
c	2	3

 

Select top N number of records:

In [18]:

n = 5
data_frame.head(n)

Out[18]:

	rev	test_col	another_col
a	0	3	0
b	1	3	1
c	2	3	2
d	3	3	3
e	4	3	4

 

Select bottom N number of records:

In [19]:

n = 5
data_frame.tail(5)

Out[19]:

	rev	test_col	another_col
f	5	3	5
g	6	3	6
h	7	3	7
i	8	3	8
j	9	3	9