pandas 기본문법과 함수

최초 작성일 : 2021-11-06
categories: Pandas

---

-판다스(pandas) 불러오기

import pandas as pd
print(pd.__version__)

1.1.5

-테스트

df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
print(type(df))

<class 'pandas.core.frame.DataFrame'>

-데이터 둘러보기

lemonade.head(5)

	Date	Location	Lemon	Orange	Temperature	Leaflets	Price
0	7/1/2016	Park	97	67	70	90.0	0.25
1	7/2/2016	Park	98	67	72	90.0	0.25
2	7/3/2016	Park	110	77	71	104.0	0.25
3	7/4/2016	Beach	134	99	76	98.0	0.25
4	7/5/2016	Beach	159	118	78	135.0	0.25

lemonade.tail(3)

	Date	Location	Lemon	Orange	Temperature	Leaflets	Price
29	7/29/2016	Park	100	66	81	95.0	0.35
30	7/30/2016	Beach	88	57	82	81.0	0.35
31	7/31/2016	Beach	76	47	82	68.0	0.35

print(lemonade.info())

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 32 entries, 0 to 31
Data columns (total 7 columns):
 #   Column       Non-Null Count  Dtype  
---  ------       --------------  -----  
 0   Date         31 non-null     object 
 1   Location     32 non-null     object 
 2   Lemon        32 non-null     int64  
 3   Orange       32 non-null     int64  
 4   Temperature  32 non-null     int64  
 5   Leaflets     31 non-null     float64
 6   Price        32 non-null     float64
dtypes: float64(2), int64(3), object(2)
memory usage: 1.9+ KB
None

lemonade.describe()

	Lemon	Orange	Temperature	Leaflets	Price
count	32.000000	32.000000	32.000000	31.000000	32.000000
mean	116.156250	80.000000	78.968750	108.548387	0.354687
std	25.823357	21.863211	4.067847	20.117718	0.113137
min	71.000000	42.000000	70.000000	68.000000	0.250000
25%	98.000000	66.750000	77.000000	90.000000	0.250000
50%	113.500000	76.500000	80.500000	108.000000	0.350000
75%	131.750000	95.000000	82.000000	124.000000	0.500000
max	176.000000	129.000000	84.000000	158.000000	0.500000

lemonade['Location'].value_counts()

Beach    17
Park     15
Name: Location, dtype: int64

-데이터 다뤄보기

lemonade['Sold'] = 0 
print(lemonade.head(3))

       Date Location  Lemon  Orange  Temperature  Leaflets  Price  Sold
0  7/1/2016     Park     97      67           70      90.0   0.25     0
1  7/2/2016     Park     98      67           72      90.0   0.25     0
2  7/3/2016     Park    110      77           71     104.0   0.25     0

lemonade['Sold'] = lemonade['Lemon'] + lemonade['Orange']
print(lemonade.head(3))

       Date Location  Lemon  Orange  Temperature  Leaflets  Price  Sold
0  7/1/2016     Park     97      67           70      90.0   0.25   164
1  7/2/2016     Park     98      67           72      90.0   0.25   165
2  7/3/2016     Park    110      77           71     104.0   0.25   187

-데이터 인덱싱

print(lemonade[0:5])

       Date Location  Lemon  Orange  Temperature  Leaflets  Price  Sold
0  7/1/2016     Park     97      67           70      90.0   0.25   164
1  7/2/2016     Park     98      67           72      90.0   0.25   165
2  7/3/2016     Park    110      77           71     104.0   0.25   187
3  7/4/2016    Beach    134      99           76      98.0   0.25   233
4  7/5/2016    Beach    159     118           78     135.0   0.25   277

lemonade['Location'] == 'Beach'

0     False
1     False
2     False
3      True
4      True
5      True
6      True
7      True
8      True
9      True
10     True
11     True
12     True
13     True
14     True
15     True
16     True
17     True
18    False
19    False
20    False
21    False
22    False
23    False
24    False
25    False
26    False
27    False
28    False
29    False
30     True
31     True
Name: Location, dtype: bool

print(lemonade[lemonade['Location'] == 'Beach'].head(3))

       Date Location  Lemon  Orange  Temperature  Leaflets  Price  Sold
3  7/4/2016    Beach    134      99           76      98.0   0.25   233
4  7/5/2016    Beach    159     118           78     135.0   0.25   277
5  7/6/2016    Beach    103      69           82      90.0   0.25   172

-기본 데이터 전처리

print(lemonade.sort_values(by=['Temperature']).head(5))

         Date Location  Lemon  Orange  Temperature  Leaflets  Price  Sold
0    7/1/2016     Park     97      67           70      90.0   0.25   164
20  7/20/2016     Park     71      42           70       NaN   0.50   113
2    7/3/2016     Park    110      77           71     104.0   0.25   187
1    7/2/2016     Park     98      67           72      90.0   0.25   165
16  7/16/2016    Beach     81      50           74      90.0   0.50   131

lemonade.sort_values(by=['Temperature', 'Orange'], ascending= False, inplace = True)
print(lemonade.loc[:,['Date','Temperature', 'Orange']].head(5))

         Date  Temperature  Orange
25  7/25/2016           84     113
12  7/12/2016           84      95
26  7/26/2016           83     129
11  7/11/2016           83     120
10  7/10/2016           82      98

print(lemonade.groupby(by='Location').count())

          Date  Lemon  Orange  Temperature  Leaflets  Price  Sold
Location                                                         
Beach       16     17      17           17        17     17    17
Park        15     15      15           15        14     15    15

print(lemonade.groupby('Location')['Price'].agg([max,min]))

          max   min
Location           
Beach     0.5  0.25
Park      0.5  0.25