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Commit e6f3fecc authored by Young Woo Kim's avatar Young Woo Kim
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Python Numpy, Pandas 예제파일/Pandas_예제.ipynb 0 → 100644
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%% Cell type:code id: tags:
``` python
import pandas as pd
import numpy as np
```
%% Cell type:code id: tags:
``` python
data = {'name': ['YoungWoo', 'DomgHo', 'Minsu', 'Hong', 'Kwangsung'],
'year': [2013, 2014, 2015, 2016, 2015],
'points': [1.5, 1.7, 3.6, 2.4, 2.9]}
df = pd.DataFrame(data)
print (df)
```
%% Output
name year points
0 YoungWoo 2013 1.5
1 DomgHo 2014 1.7
2 Minsu 2015 3.6
3 Hong 2016 2.4
4 Kwangsung 2015 2.9
%% Cell type:code id: tags:
``` python
df
```
%% Output
name year points
0 YoungWoo 2013 1.5
1 DomgHo 2014 1.7
2 Minsu 2015 3.6
3 Hong 2016 2.4
4 Kwangsung 2015 2.9
%% Cell type:code id: tags:
``` python
csv = pd.read_csv('C:/Users/김영우/jupyter/example.csv')
csv
```
%% Output
ID NAME 나이 점수
0 1 Kim 23 75
1 2 Lee 19 80
2 3 Choi 20 59
3 4 Song 23 90
4 5 Hwang 25 83
%% Cell type:code id: tags:
``` python
print (df.columns)
print (csv.columns)
```
%% Output
Index(['name', 'year', 'points'], dtype='object')
Index(['ID', 'NAME', '나이', '점수'], dtype='object')
%% Cell type:code id: tags:
``` python
print (df.values)
print (csv.values)
```
%% Output
[['YoungWoo' 2013 1.5]
['DomgHo' 2014 1.7]
['Minsu' 2015 3.6]
['Hong' 2016 2.4]
['Kwangsung' 2015 2.9]]
[[1 'Kim' 23 75]
[2 'Lee' 19 80]
[3 'Choi' 20 59]
[4 'Song' 23 90]
[5 'Hwang' 25 83]]
%% Cell type:code id: tags:
``` python
df.describe()
```
%% Output
year points
count 5.000000 5.000000
mean 2014.600000 2.420000
std 1.140175 0.864292
min 2013.000000 1.500000
25% 2014.000000 1.700000
50% 2015.000000 2.400000
75% 2015.000000 2.900000
max 2016.000000 3.600000
%% Cell type:code id: tags:
``` python
csv.describe()
```
%% Output
ID 나이 점수
count 5.000000 5.00000 5.000000
mean 3.000000 22.00000 77.400000
std 1.581139 2.44949 11.631853
min 1.000000 19.00000 59.000000
25% 2.000000 20.00000 75.000000
50% 3.000000 23.00000 80.000000
75% 4.000000 23.00000 83.000000
max 5.000000 25.00000 90.000000
%% Cell type:code id: tags:
``` python
df['zero'] = np.zeros(5)
df
```
%% Output
name year points zero
0 YoungWoo 2013 1.5 0.0
1 DomgHo 2014 1.7 0.0
2 Minsu 2015 3.6 0.0
3 Hong 2016 2.4 0.0
4 Kwangsung 2015 2.9 0.0
%% Cell type:code id: tags:
``` python
csv['random'] = np.random.rand(5)
csv['random'] *= 10
csv
```
%% Output
ID NAME 나이 점수 random
0 1 Kim 23 75 1.859625
1 2 Lee 19 80 0.588391
2 3 Choi 20 59 8.702442
3 4 Song 23 90 7.638486
4 5 Hwang 25 83 9.592227
%% Cell type:code id: tags:
``` python
del df['zero']
df
```
%% Output
name year points
0 YoungWoo 2013 1.5
1 DomgHo 2014 1.7
2 Minsu 2015 3.6
3 Hong 2016 2.4
4 Kwangsung 2015 2.9
%% Cell type:code id: tags:
``` python
val = pd.Series([10, 20, 30, 40, 50])
df['tens'] = val
df
```
%% Output
name year points tens
0 YoungWoo 2013 1.5 10
1 DomgHo 2014 1.7 20
2 Minsu 2015 3.6 30
3 Hong 2016 2.4 40
4 Kwangsung 2015 2.9 50
%% Cell type:code id: tags:
``` python
print (df.sum(axis = 0))
print (df.sum(axis = 1))
print (df.min(axis = 0))
```
%% Output
name YoungWooDomgHoMinsuHongKwangsung
year 10073
points 12.1
tens 150
dtype: object
0 2024.5
1 2035.7
2 2048.6
3 2058.4
4 2067.9
dtype: float64
name DomgHo
year 2013
points 1.5
tens 10
dtype: object
%% Cell type:code id: tags:
``` python
```
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