Pandas 기초 1

In [1]:

!conda list | grep pandas

pandas                    1.2.1            py38hb2f4e1b_0  

In [2]:

!import pandas as pd

In [3]:

df = pd.read_csv('desktop/friend_list.csv')

In [4]:

df

Out[4]:

	name	age	job
0	John	20	student
1	Jenny	30	developer
2	Nate	30	teacher
3	Julia	40	dentist
4	Brian	45	manager
5	Chris	25	intern

In [5]:

# 앞 두개만 출력
df.head(2)

Out[5]:

	name	age	job
0	John	20	student
1	Jenny	30	developer

In [6]:

#끝 세개만 출력
df.tail(3)

Out[6]:

	name	age	job
3	Julia	40	dentist
4	Brian	45	manager
5	Chris	25	intern

In [15]:

#탭으로 데이터 구분시 그것을 알려주기 위한 코드
df = pd.read_csv('desktop/friend_list_tab.csv', delimiter = '\t')

In [16]:

df

Out[16]:

	John	20	student
0	jenny	30	developer
1	nate	30	teacher
2	julia	40	dentist
3	brian	45	manager
4	chris	25	intern

In [17]:

#데이터에 제목 없을때
df = pd.read_csv('desktop/friend_list_tab.csv', delimiter = '\t', header = None)

In [18]:

df

Out[18]:

	0	1	2
0	John	20	student
1	jenny	30	developer
2	nate	30	teacher
3	julia	40	dentist
4	brian	45	manager
5	chris	25	intern

In [19]:

# 헤더정보 넣기
df.columns = ['name', 'age', 'job']

In [20]:

df

Out[20]:

	name	age	job
0	John	20	student
1	jenny	30	developer
2	nate	30	teacher
3	julia	40	dentist
4	brian	45	manager
5	chris	25	intern

In [21]:

#한번에 헤더정보 넣기
df = pd.read_csv('desktop/friend_list_tab.csv', delimiter = '\t', header = None, names = ['name', 'age', 'job'])

In [22]:

df

Out[22]:

	name	age	job
0	John	20	student
1	jenny	30	developer
2	nate	30	teacher
3	julia	40	dentist
4	brian	45	manager
5	chris	25	intern

In [ ]:

In [1]:

!conda list | grep pandas

pandas                    1.2.1            py38hb2f4e1b_0  

In [2]:

!import pandas as pd

In [3]:

df = pd.read_csv('desktop/friend_list.csv')

In [4]:

df

Out[4]:

	name	age	job
0	John	20	student
1	Jenny	30	developer
2	Nate	30	teacher
3	Julia	40	dentist
4	Brian	45	manager
5	Chris	25	intern

In [5]:

# 앞 두개만 출력
df.head(2)

Out[5]:

	name	age	job
0	John	20	student
1	Jenny	30	developer

In [6]:

#끝 세개만 출력
df.tail(3)

Out[6]:

	name	age	job
3	Julia	40	dentist
4	Brian	45	manager
5	Chris	25	intern

In [15]:

#탭으로 데이터 구분시 그것을 알려주기 위한 코드
df = pd.read_csv('desktop/friend_list_tab.csv', delimiter = '\t')

In [16]:

df

Out[16]:

	John	20	student
0	jenny	30	developer
1	nate	30	teacher
2	julia	40	dentist
3	brian	45	manager
4	chris	25	intern

In [17]:

#데이터에 제목 없을때
df = pd.read_csv('desktop/friend_list_tab.csv', delimiter = '\t', header = None)

In [18]:

df

Out[18]:

	0	1	2
0	John	20	student
1	jenny	30	developer
2	nate	30	teacher
3	julia	40	dentist
4	brian	45	manager
5	chris	25	intern

In [19]:

# 헤더정보 넣기
df.columns = ['name', 'age', 'job']

In [20]:

df

Out[20]:

	name	age	job
0	John	20	student
1	jenny	30	developer
2	nate	30	teacher
3	julia	40	dentist
4	brian	45	manager
5	chris	25	intern

In [21]:

#한번에 헤더정보 넣기
df = pd.read_csv('desktop/friend_list_tab.csv', delimiter = '\t', header = None, names = ['name', 'age', 'job'])

In [22]:

df

Out[22]:

	name	age	job
0	John	20	student
1	jenny	30	developer
2	nate	30	teacher
3	julia	40	dentist
4	brian	45	manager
5	chris	25	intern

In [ ]: