Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells20073
Missing cells (%)12.5%
Duplicate rows1684
Duplicate rows (%)16.8%
Total size in memory1.3 MiB
Average record size in memory141.0 B

Variable types

Categorical4
Numeric5
DateTime1
Text5
Boolean1

Dataset

Description식품위생등급 평가관리 내역
Author식품의약품안전처
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=UH5QGLDBDVIK451GMJG129788158&infSeq=1

Alerts

점검불가여부 has constant value ""Constant
Dataset has 1684 (16.8%) duplicate rowsDuplicates
평가점수 is highly overall correlated with 평가등급High correlation
위도 is highly overall correlated with 시군명High correlation
경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
평가유형구분 is highly overall correlated with 시군명High correlation
평가등급 is highly overall correlated with 평가점수High correlation
업소위치 is highly overall correlated with 시군명High correlation
평가유형구분 is highly imbalanced (77.1%)Imbalance
평가계획일자 has 9595 (96.0%) missing valuesMissing
점검불가여부 has 9938 (99.4%) missing valuesMissing
소재지도로명주소 has 268 (2.7%) missing valuesMissing

Reproduction

Analysis started2023-12-10 21:22:42.083161
Analysis finished2023-12-10 21:22:47.814616
Duration5.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
고양시
969 
용인시
864 
포천시
761 
광주시
755 
김포시
672 
Other values (26)
5979 

Length

Max length4
Median length3
Mean length3.0325
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광주시
2nd row용인시
3rd row안성시
4th row용인시
5th row이천시

Common Values

ValueCountFrequency (%)
고양시 969
 
9.7%
용인시 864
 
8.6%
포천시 761
 
7.6%
광주시 755
 
7.5%
김포시 672
 
6.7%
파주시 622
 
6.2%
수원시 597
 
6.0%
화성시 560
 
5.6%
부천시 497
 
5.0%
하남시 463
 
4.6%
Other values (21) 3240
32.4%

Length

2023-12-11T06:22:47.876216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고양시 969
 
9.7%
용인시 864
 
8.6%
포천시 761
 
7.6%
광주시 755
 
7.5%
김포시 672
 
6.7%
파주시 622
 
6.2%
수원시 597
 
6.0%
화성시 560
 
5.6%
부천시 497
 
5.0%
하남시 463
 
4.6%
Other values (21) 3240
32.4%

평가일련번호
Real number (ℝ)

Distinct8133
Distinct (%)81.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33966.485
Minimum7
Maximum59391
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:22:47.990295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile5406.9
Q122575.5
median37112.5
Q346493.5
95-th percentile54844.05
Maximum59391
Range59384
Interquartile range (IQR)23918

Descriptive statistics

Standard deviation15459.143
Coefficient of variation (CV)0.45512933
Kurtosis-0.82666278
Mean33966.485
Median Absolute Deviation (MAD)11268.5
Skewness-0.47976256
Sum3.3966485 × 108
Variance2.3898511 × 108
MonotonicityNot monotonic
2023-12-11T06:22:48.102942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25113 6
 
0.1%
24731 6
 
0.1%
25291 6
 
0.1%
24897 6
 
0.1%
24841 6
 
0.1%
24965 5
 
0.1%
24809 5
 
0.1%
24663 5
 
0.1%
24044 5
 
0.1%
23963 5
 
0.1%
Other values (8123) 9945
99.5%
ValueCountFrequency (%)
7 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
25 1
< 0.1%
30 1
< 0.1%
33 1
< 0.1%
34 1
< 0.1%
35 1
< 0.1%
39 1
< 0.1%
40 1
< 0.1%
ValueCountFrequency (%)
59391 1
< 0.1%
59387 1
< 0.1%
59385 1
< 0.1%
59381 1
< 0.1%
59380 1
< 0.1%
59379 1
< 0.1%
59303 1
< 0.1%
59302 1
< 0.1%
59300 1
< 0.1%
59298 1
< 0.1%

평가계획일자
Date

MISSING 

Distinct158
Distinct (%)39.0%
Missing9595
Missing (%)96.0%
Memory size156.2 KiB
Minimum2015-05-29 00:00:00
Maximum2021-03-04 00:00:00
2023-12-11T06:22:48.210056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:48.319188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

평가유형구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9378 
정기평가
 
565
신규평가
 
57

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9378
93.8%
정기평가 565
 
5.7%
신규평가 57
 
0.6%

Length

2023-12-11T06:22:48.427038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:22:48.499763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9378
93.8%
정기평가 565
 
5.7%
신규평가 57
 
0.6%

평가일자
Text

Distinct1819
Distinct (%)18.3%
Missing73
Missing (%)0.7%
Memory size156.2 KiB
2023-12-11T06:22:48.698893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters99270
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique316 ?
Unique (%)3.2%

Sample

1st row2014-04-18
2nd row2016-07-26
3rd row2018-11-15
4th row2019-09-03
5th row2014-10-17
ValueCountFrequency (%)
2017-11-01 185
 
1.9%
2018-10-30 94
 
0.9%
2016-12-23 76
 
0.8%
2019-06-04 47
 
0.5%
2015-12-11 43
 
0.4%
2020-08-24 40
 
0.4%
2019-03-25 29
 
0.3%
2019-06-18 29
 
0.3%
2019-10-18 28
 
0.3%
2019-12-31 28
 
0.3%
Other values (1809) 9328
94.0%
2023-12-11T06:22:49.012109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22166
22.3%
- 19854
20.0%
1 18898
19.0%
2 17060
17.2%
9 3846
 
3.9%
8 3269
 
3.3%
7 3244
 
3.3%
6 3237
 
3.3%
3 2788
 
2.8%
5 2710
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79416
80.0%
Dash Punctuation 19854
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22166
27.9%
1 18898
23.8%
2 17060
21.5%
9 3846
 
4.8%
8 3269
 
4.1%
7 3244
 
4.1%
6 3237
 
4.1%
3 2788
 
3.5%
5 2710
 
3.4%
4 2198
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 19854
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99270
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22166
22.3%
- 19854
20.0%
1 18898
19.0%
2 17060
17.2%
9 3846
 
3.9%
8 3269
 
3.3%
7 3244
 
3.3%
6 3237
 
3.3%
3 2788
 
2.8%
5 2710
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99270
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22166
22.3%
- 19854
20.0%
1 18898
19.0%
2 17060
17.2%
9 3846
 
3.9%
8 3269
 
3.3%
7 3244
 
3.3%
6 3237
 
3.3%
3 2788
 
2.8%
5 2710
 
2.7%

평가점수
Real number (ℝ)

HIGH CORRELATION 

Distinct199
Distinct (%)2.0%
Missing29
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean130.60766
Minimum-246
Maximum200
Zeros61
Zeros (%)0.6%
Negative34
Negative (%)0.3%
Memory size166.0 KiB
2023-12-11T06:22:49.130782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-246
5-th percentile86
Q1110
median125
Q3156
95-th percentile189
Maximum200
Range446
Interquartile range (IQR)46

Descriptive statistics

Standard deviation35.21862
Coefficient of variation (CV)0.26965202
Kurtosis6.0781328
Mean130.60766
Median Absolute Deviation (MAD)20
Skewness-0.88043274
Sum1302289
Variance1240.3512
MonotonicityNot monotonic
2023-12-11T06:22:49.248529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
114 439
 
4.4%
113 200
 
2.0%
111 196
 
2.0%
110 185
 
1.8%
109 182
 
1.8%
120 171
 
1.7%
118 170
 
1.7%
119 167
 
1.7%
116 165
 
1.7%
108 154
 
1.5%
Other values (189) 7942
79.4%
ValueCountFrequency (%)
-246 1
 
< 0.1%
-243 1
 
< 0.1%
-190 2
< 0.1%
-114 2
< 0.1%
-96 1
 
< 0.1%
-94 1
 
< 0.1%
-78 2
< 0.1%
-59 1
 
< 0.1%
-57 4
< 0.1%
-52 1
 
< 0.1%
ValueCountFrequency (%)
200 96
1.0%
199 3
 
< 0.1%
198 13
 
0.1%
197 70
0.7%
196 8
 
0.1%
195 47
0.5%
194 58
0.6%
193 22
 
0.2%
192 44
0.4%
191 41
0.4%

평가등급
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반관리업소
6514 
자율관리업소
2846 
중점관리업소
 
577
<NA>
 
63

Length

Max length6
Median length6
Mean length5.9874
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자율관리업소
2nd row자율관리업소
3rd row일반관리업소
4th row중점관리업소
5th row일반관리업소

Common Values

ValueCountFrequency (%)
일반관리업소 6514
65.1%
자율관리업소 2846
28.5%
중점관리업소 577
 
5.8%
<NA> 63
 
0.6%

Length

2023-12-11T06:22:49.375973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:22:49.464257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반관리업소 6514
65.1%
자율관리업소 2846
28.5%
중점관리업소 577
 
5.8%
na 63
 
0.6%

업소위치
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4194 
도시
1898 
농어촌.산간
1701 
기타
1582 
공단
625 

Length

Max length6
Median length4
Mean length3.5192
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row도시
3rd row<NA>
4th row<NA>
5th row농어촌.산간

Common Values

ValueCountFrequency (%)
<NA> 4194
41.9%
도시 1898
19.0%
농어촌.산간 1701
17.0%
기타 1582
 
15.8%
공단 625
 
6.2%

Length

2023-12-11T06:22:49.552338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:22:49.643966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4194
41.9%
도시 1898
19.0%
농어촌.산간 1701
17.0%
기타 1582
 
15.8%
공단 625
 
6.2%

인허가번호
Real number (ℝ)

Distinct4996
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0088148 × 1010
Minimum1.9630364 × 1010
Maximum2.0200361 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:22:49.739220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9630364 × 1010
5-th percentile1.9930372 × 1010
Q12.0050358 × 1010
median2.0110345 × 1010
Q32.014037 × 1010
95-th percentile2.0180017 × 1010
Maximum2.0200361 × 1010
Range5.69997 × 108
Interquartile range (IQR)90012353

Descriptive statistics

Standard deviation81387363
Coefficient of variation (CV)0.0040515114
Kurtosis4.0076475
Mean2.0088148 × 1010
Median Absolute Deviation (MAD)40016788
Skewness-1.700736
Sum2.0088148 × 1014
Variance6.6239029 × 1015
MonotonicityNot monotonic
2023-12-11T06:22:50.060591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20060015057 13
 
0.1%
20130017080 11
 
0.1%
20110015103 10
 
0.1%
20080015264 9
 
0.1%
20150006107 8
 
0.1%
20060015045 8
 
0.1%
20130017053 8
 
0.1%
20130015142 8
 
0.1%
20180007276 7
 
0.1%
19820263003 7
 
0.1%
Other values (4986) 9911
99.1%
ValueCountFrequency (%)
19630364001 1
 
< 0.1%
19670294001 1
 
< 0.1%
19670347001 3
< 0.1%
19690288004 2
< 0.1%
19690320001 2
< 0.1%
19690364004 3
< 0.1%
19700263001 2
< 0.1%
19700285006 3
< 0.1%
19700347001 1
 
< 0.1%
19700362001 1
 
< 0.1%
ValueCountFrequency (%)
20200361006 2
< 0.1%
20200004155 1
< 0.1%
20200003986 2
< 0.1%
20200002962 1
< 0.1%
20200002446 2
< 0.1%
20190393189 1
< 0.1%
20190393118 2
< 0.1%
20190387275 1
< 0.1%
20190385692 2
< 0.1%
20190385314 1
< 0.1%

업체명
Text

Distinct4795
Distinct (%)47.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:22:50.282658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length31
Mean length7.2985
Min length2

Characters and Unicode

Total characters72985
Distinct characters821
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2062 ?
Unique (%)20.6%

Sample

1st row(주)대정에프엔디
2nd row오션나라
3rd row착한마을사람들
4th row텃밭한아름 영농조합법인
5th row주식회사 동일제빙
ValueCountFrequency (%)
주식회사 929
 
7.5%
농업회사법인 299
 
2.4%
주 40
 
0.3%
coffee 38
 
0.3%
영농조합법인 34
 
0.3%
동네방네 28
 
0.2%
food 28
 
0.2%
양조장 27
 
0.2%
제2공장 24
 
0.2%
커피 24
 
0.2%
Other values (5039) 10884
88.1%
2023-12-11T06:22:50.632350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 4812
 
6.6%
) 3475
 
4.8%
( 3456
 
4.7%
식 3210
 
4.4%
2355
 
3.2%
사 2033
 
2.8%
품 1981
 
2.7%
회 1806
 
2.5%
드 1534
 
2.1%
푸 1335
 
1.8%
Other values (811) 46988
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60838
83.4%
Close Punctuation 3475
 
4.8%
Open Punctuation 3456
 
4.7%
Space Separator 2355
 
3.2%
Uppercase Letter 1354
 
1.9%
Lowercase Letter 1057
 
1.4%
Decimal Number 217
 
0.3%
Other Punctuation 177
 
0.2%
Other Symbol 46
 
0.1%
Dash Punctuation 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 4812
 
7.9%
식 3210
 
5.3%
사 2033
 
3.3%
품 1981
 
3.3%
회 1806
 
3.0%
드 1534
 
2.5%
푸 1335
 
2.2%
이 1262
 
2.1%
스 1254
 
2.1%
농 1117
 
1.8%
Other values (739) 40494
66.6%
Uppercase Letter
ValueCountFrequency (%)
F 232
17.1%
O 128
 
9.5%
C 114
 
8.4%
S 112
 
8.3%
B 91
 
6.7%
E 91
 
6.7%
A 67
 
4.9%
D 65
 
4.8%
R 56
 
4.1%
K 49
 
3.6%
Other values (16) 349
25.8%
Lowercase Letter
ValueCountFrequency (%)
e 190
18.0%
o 150
14.2%
a 106
10.0%
f 85
 
8.0%
r 59
 
5.6%
n 56
 
5.3%
c 53
 
5.0%
s 48
 
4.5%
t 48
 
4.5%
i 36
 
3.4%
Other values (14) 226
21.4%
Decimal Number
ValueCountFrequency (%)
2 97
44.7%
1 43
19.8%
3 17
 
7.8%
0 13
 
6.0%
9 12
 
5.5%
7 9
 
4.1%
5 9
 
4.1%
8 8
 
3.7%
6 5
 
2.3%
4 4
 
1.8%
Other Punctuation
ValueCountFrequency (%)
& 97
54.8%
. 43
24.3%
' 16
 
9.0%
/ 10
 
5.6%
· 7
 
4.0%
＆ 3
 
1.7%
, 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 3475
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3456
100.0%
Space Separator
ValueCountFrequency (%)
2355
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60866
83.4%
Common 9690
 
13.3%
Latin 2411
 
3.3%
Han 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 4812
 
7.9%
식 3210
 
5.3%
사 2033
 
3.3%
품 1981
 
3.3%
회 1806
 
3.0%
드 1534
 
2.5%
푸 1335
 
2.2%
이 1262
 
2.1%
스 1254
 
2.1%
농 1117
 
1.8%
Other values (735) 40522
66.6%
Latin
ValueCountFrequency (%)
F 232
 
9.6%
e 190
 
7.9%
o 150
 
6.2%
O 128
 
5.3%
C 114
 
4.7%
S 112
 
4.6%
a 106
 
4.4%
B 91
 
3.8%
E 91
 
3.8%
f 85
 
3.5%
Other values (40) 1112
46.1%
Common
ValueCountFrequency (%)
) 3475
35.9%
( 3456
35.7%
2355
24.3%
2 97
 
1.0%
& 97
 
1.0%
1 43
 
0.4%
. 43
 
0.4%
3 17
 
0.2%
' 16
 
0.2%
0 13
 
0.1%
Other values (11) 78
 
0.8%
Han
ValueCountFrequency (%)
名 4
22.2%
皓 4
22.2%
食 4
22.2%
品 4
22.2%
色 2
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60814
83.3%
ASCII 12091
 
16.6%
None 56
 
0.1%
CJK 18
 
< 0.1%
Compat Jamo 6
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 4812
 
7.9%
식 3210
 
5.3%
사 2033
 
3.3%
품 1981
 
3.3%
회 1806
 
3.0%
드 1534
 
2.5%
푸 1335
 
2.2%
이 1262
 
2.1%
스 1254
 
2.1%
농 1117
 
1.8%
Other values (733) 40470
66.5%
ASCII
ValueCountFrequency (%)
) 3475
28.7%
( 3456
28.6%
2355
19.5%
F 232
 
1.9%
e 190
 
1.6%
o 150
 
1.2%
O 128
 
1.1%
C 114
 
0.9%
S 112
 
0.9%
a 106
 
0.9%
Other values (59) 1773
14.7%
None
ValueCountFrequency (%)
㈜ 46
82.1%
· 7
 
12.5%
＆ 3
 
5.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 6
100.0%
CJK
ValueCountFrequency (%)
名 4
22.2%
皓 4
22.2%
食 4
22.2%
品 4
22.2%
色 2
11.1%

대표자명
Text

Distinct3824
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:22:50.966787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length3
Mean length3.1835
Min length2

Characters and Unicode

Total characters31835
Distinct characters326
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1994 ?
Unique (%)19.9%

Sample

1st row박환국
2nd row김*두
3rd row최*선
4th row이*엽
5th row서대원
ValueCountFrequency (%)
외 279
 
2.6%
1명 273
 
2.6%
김*호 59
 
0.6%
김*수 55
 
0.5%
이*우 55
 
0.5%
김*희 51
 
0.5%
이*숙 49
 
0.5%
김*순 48
 
0.5%
이*호 45
 
0.4%
이*영 43
 
0.4%
Other values (3752) 9660
91.0%
2023-12-11T06:22:51.499074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 7059
22.2%
김 2152
 
6.8%
이 1698
 
5.3%
박 794
 
2.5%
정 703
 
2.2%
617
 
1.9%
최 467
 
1.5%
영 452
 
1.4%
호 420
 
1.3%
명 389
 
1.2%
Other values (316) 17084
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23690
74.4%
Other Punctuation 7079
 
22.2%
Space Separator 617
 
1.9%
Decimal Number 282
 
0.9%
Uppercase Letter 151
 
0.5%
Close Punctuation 8
 
< 0.1%
Open Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 2152
 
9.1%
이 1698
 
7.2%
박 794
 
3.4%
정 703
 
3.0%
최 467
 
2.0%
영 452
 
1.9%
호 420
 
1.8%
명 389
 
1.6%
수 361
 
1.5%
희 361
 
1.5%
Other values (286) 15893
67.1%
Uppercase Letter
ValueCountFrequency (%)
A 20
13.2%
N 18
11.9%
O 12
 
7.9%
G 11
 
7.3%
H 11
 
7.3%
L 10
 
6.6%
E 9
 
6.0%
I 8
 
5.3%
D 8
 
5.3%
M 5
 
3.3%
Other values (12) 39
25.8%
Other Punctuation
ValueCountFrequency (%)
* 7059
99.7%
, 19
 
0.3%
. 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 275
97.5%
2 7
 
2.5%
Space Separator
ValueCountFrequency (%)
617
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23690
74.4%
Common 7994
 
25.1%
Latin 151
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 2152
 
9.1%
이 1698
 
7.2%
박 794
 
3.4%
정 703
 
3.0%
최 467
 
2.0%
영 452
 
1.9%
호 420
 
1.8%
명 389
 
1.6%
수 361
 
1.5%
희 361
 
1.5%
Other values (286) 15893
67.1%
Latin
ValueCountFrequency (%)
A 20
13.2%
N 18
11.9%
O 12
 
7.9%
G 11
 
7.3%
H 11
 
7.3%
L 10
 
6.6%
E 9
 
6.0%
I 8
 
5.3%
D 8
 
5.3%
M 5
 
3.3%
Other values (12) 39
25.8%
Common
ValueCountFrequency (%)
* 7059
88.3%
617
 
7.7%
1 275
 
3.4%
, 19
 
0.2%
) 8
 
0.1%
( 8
 
0.1%
2 7
 
0.1%
. 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23690
74.4%
ASCII 8145
 
25.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 7059
86.7%
617
 
7.6%
1 275
 
3.4%
A 20
 
0.2%
, 19
 
0.2%
N 18
 
0.2%
O 12
 
0.1%
G 11
 
0.1%
H 11
 
0.1%
L 10
 
0.1%
Other values (20) 93
 
1.1%
Hangul
ValueCountFrequency (%)
김 2152
 
9.1%
이 1698
 
7.2%
박 794
 
3.4%
정 703
 
3.0%
최 467
 
2.0%
영 452
 
1.9%
호 420
 
1.8%
명 389
 
1.6%
수 361
 
1.5%
희 361
 
1.5%
Other values (286) 15893
67.1%

점검불가여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.6%
Missing9938
Missing (%)99.4%
Memory size97.7 KiB
True
 
62
(Missing)
9938 
ValueCountFrequency (%)
True 62
 
0.6%
(Missing) 9938
99.4%
2023-12-11T06:22:51.636218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

소재지도로명주소
Text

MISSING 

Distinct4389
Distinct (%)45.1%
Missing268
Missing (%)2.7%
Memory size156.2 KiB
2023-12-11T06:22:51.961483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length20.959823
Min length13

Characters and Unicode

Total characters203981
Distinct characters412
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1804 ?
Unique (%)18.5%

Sample

1st row경기도 광주시 오포읍 봉골길81번길 11-12
2nd row경기도 용인시 기흥구 신정로 203
3rd row경기도 안성시 대덕면 한사울길 125-50
4th row경기도 용인시 처인구 남사면 원암로91번길 9
5th row경기도 이천시 신둔면 경충대로 3035
ValueCountFrequency (%)
경기도 9732
 
21.0%
고양시 947
 
2.0%
용인시 852
 
1.8%
포천시 751
 
1.6%
광주시 733
 
1.6%
김포시 660
 
1.4%
파주시 600
 
1.3%
수원시 575
 
1.2%
화성시 551
 
1.2%
처인구 530
 
1.1%
Other values (4969) 30504
65.7%
2023-12-11T06:22:52.551981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36703
 
18.0%
도 10129
 
5.0%
기 10124
 
5.0%
경 9971
 
4.9%
시 9872
 
4.8%
1 8127
 
4.0%
로 7907
 
3.9%
길 5892
 
2.9%
2 5884
 
2.9%
3 4337
 
2.1%
Other values (402) 95035
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 123581
60.6%
Decimal Number 40182
 
19.7%
Space Separator 36703
 
18.0%
Dash Punctuation 3509
 
1.7%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 10129
 
8.2%
기 10124
 
8.2%
경 9971
 
8.1%
시 9872
 
8.0%
로 7907
 
6.4%
길 5892
 
4.8%
번 4003
 
3.2%
구 2945
 
2.4%
면 2856
 
2.3%
양 2544
 
2.1%
Other values (389) 57338
46.4%
Decimal Number
ValueCountFrequency (%)
1 8127
20.2%
2 5884
14.6%
3 4337
10.8%
4 3928
9.8%
5 3592
8.9%
6 3381
8.4%
7 3013
 
7.5%
8 2799
 
7.0%
0 2620
 
6.5%
9 2501
 
6.2%
Space Separator
ValueCountFrequency (%)
36703
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3509
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 123581
60.6%
Common 80400
39.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 10129
 
8.2%
기 10124
 
8.2%
경 9971
 
8.1%
시 9872
 
8.0%
로 7907
 
6.4%
길 5892
 
4.8%
번 4003
 
3.2%
구 2945
 
2.4%
면 2856
 
2.3%
양 2544
 
2.1%
Other values (389) 57338
46.4%
Common
ValueCountFrequency (%)
36703
45.7%
1 8127
 
10.1%
2 5884
 
7.3%
3 4337
 
5.4%
4 3928
 
4.9%
5 3592
 
4.5%
- 3509
 
4.4%
6 3381
 
4.2%
7 3013
 
3.7%
8 2799
 
3.5%
Other values (3) 5127
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123581
60.6%
ASCII 80400
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36703
45.7%
1 8127
 
10.1%
2 5884
 
7.3%
3 4337
 
5.4%
4 3928
 
4.9%
5 3592
 
4.5%
- 3509
 
4.4%
6 3381
 
4.2%
7 3013
 
3.7%
8 2799
 
3.5%
Other values (3) 5127
 
6.4%
Hangul
ValueCountFrequency (%)
도 10129
 
8.2%
기 10124
 
8.2%
경 9971
 
8.1%
시 9872
 
8.0%
로 7907
 
6.4%
길 5892
 
4.8%
번 4003
 
3.2%
구 2945
 
2.4%
면 2856
 
2.3%
양 2544
 
2.1%
Other values (389) 57338
46.4%

소재지지번주소
Text

Distinct4877
Distinct (%)48.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:22:52.899967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length60
Mean length27.1583
Min length15

Characters and Unicode

Total characters271583
Distinct characters508
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2148 ?
Unique (%)21.5%

Sample

1st row경기도 광주시 오포읍 문형리 154-6번지
2nd row경기도 용인시 기흥구 신갈동 537-22번지
3rd row경기도 안성시 대덕면 삼한리 4번지
4th row경기도 용인시 처인구 남사면 원암리 137-5번지
5th row경기도 이천시 신둔면 수남리 90번지
ValueCountFrequency (%)
경기도 10017
 
17.1%
1층 1715
 
2.9%
고양시 969
 
1.7%
용인시 887
 
1.5%
광주시 768
 
1.3%
포천시 762
 
1.3%
김포시 690
 
1.2%
파주시 622
 
1.1%
수원시 597
 
1.0%
화성시 583
 
1.0%
Other values (6242) 40853
69.9%
2023-12-11T06:22:53.420958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48463
 
17.8%
1 11710
 
4.3%
지 11104
 
4.1%
도 10693
 
3.9%
기 10542
 
3.9%
시 10310
 
3.8%
동 10274
 
3.8%
경 10252
 
3.8%
번 9703
 
3.6%
- 8041
 
3.0%
Other values (498) 130491
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 160393
59.1%
Decimal Number 48480
 
17.9%
Space Separator 48463
 
17.8%
Dash Punctuation 8041
 
3.0%
Open Punctuation 1965
 
0.7%
Close Punctuation 1965
 
0.7%
Other Punctuation 1370
 
0.5%
Uppercase Letter 823
 
0.3%
Math Symbol 63
 
< 0.1%
Lowercase Letter 16
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 11104
 
6.9%
도 10693
 
6.7%
기 10542
 
6.6%
시 10310
 
6.4%
동 10274
 
6.4%
경 10252
 
6.4%
번 9703
 
6.0%
리 5037
 
3.1%
층 3483
 
2.2%
구 3169
 
2.0%
Other values (438) 75826
47.3%
Uppercase Letter
ValueCountFrequency (%)
B 230
27.9%
A 194
23.6%
C 67
 
8.1%
T 48
 
5.8%
E 42
 
5.1%
D 40
 
4.9%
I 40
 
4.9%
S 34
 
4.1%
K 29
 
3.5%
R 18
 
2.2%
Other values (14) 81
 
9.8%
Lowercase Letter
ValueCountFrequency (%)
c 3
18.8%
i 2
12.5%
n 2
12.5%
b 2
12.5%
u 1
 
6.2%
k 1
 
6.2%
l 1
 
6.2%
d 1
 
6.2%
g 1
 
6.2%
s 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 11710
24.2%
2 7208
14.9%
3 5409
11.2%
4 4369
 
9.0%
5 4114
 
8.5%
6 3572
 
7.4%
0 3362
 
6.9%
7 3226
 
6.7%
8 2859
 
5.9%
9 2651
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 1286
93.9%
. 61
 
4.5%
/ 14
 
1.0%
: 6
 
0.4%
· 3
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1964
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1964
99.9%
] 1
 
0.1%
Other Symbol
ValueCountFrequency (%)
㎡ 2
66.7%
ⓝ 1
33.3%
Space Separator
ValueCountFrequency (%)
48463
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8041
100.0%
Math Symbol
ValueCountFrequency (%)
~ 63
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 160393
59.1%
Common 110350
40.6%
Latin 840
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 11104
 
6.9%
도 10693
 
6.7%
기 10542
 
6.6%
시 10310
 
6.4%
동 10274
 
6.4%
경 10252
 
6.4%
번 9703
 
6.0%
리 5037
 
3.1%
층 3483
 
2.2%
구 3169
 
2.0%
Other values (438) 75826
47.3%
Latin
ValueCountFrequency (%)
B 230
27.4%
A 194
23.1%
C 67
 
8.0%
T 48
 
5.7%
E 42
 
5.0%
D 40
 
4.8%
I 40
 
4.8%
S 34
 
4.0%
K 29
 
3.5%
R 18
 
2.1%
Other values (26) 98
11.7%
Common
ValueCountFrequency (%)
48463
43.9%
1 11710
 
10.6%
- 8041
 
7.3%
2 7208
 
6.5%
3 5409
 
4.9%
4 4369
 
4.0%
5 4114
 
3.7%
6 3572
 
3.2%
0 3362
 
3.0%
7 3226
 
2.9%
Other values (14) 10876
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 160393
59.1%
ASCII 111183
40.9%
None 3
 
< 0.1%
CJK Compat 2
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48463
43.6%
1 11710
 
10.5%
- 8041
 
7.2%
2 7208
 
6.5%
3 5409
 
4.9%
4 4369
 
3.9%
5 4114
 
3.7%
6 3572
 
3.2%
0 3362
 
3.0%
7 3226
 
2.9%
Other values (46) 11709
 
10.5%
Hangul
ValueCountFrequency (%)
지 11104
 
6.9%
도 10693
 
6.7%
기 10542
 
6.6%
시 10310
 
6.4%
동 10274
 
6.4%
경 10252
 
6.4%
번 9703
 
6.0%
리 5037
 
3.1%
층 3483
 
2.2%
구 3169
 
2.0%
Other values (438) 75826
47.3%
None
ValueCountFrequency (%)
· 3
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓝ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct5602
Distinct (%)56.5%
Missing85
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean37.483473
Minimum36.935779
Maximum38.109138
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:22:53.584035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.935779
5-th percentile37.112132
Q137.288561
median37.440918
Q337.703153
95-th percentile37.865055
Maximum38.109138
Range1.1733585
Interquartile range (IQR)0.41459221

Descriptive statistics

Standard deviation0.24645442
Coefficient of variation (CV)0.0065750155
Kurtosis-0.97991382
Mean37.483473
Median Absolute Deviation (MAD)0.20403407
Skewness0.12127341
Sum371648.64
Variance0.060739781
MonotonicityNot monotonic
2023-12-11T06:22:53.725901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5224210033 26
 
0.3%
37.5535037868 26
 
0.3%
37.6490702916 25
 
0.2%
37.5266939005 16
 
0.2%
37.4577455956 11
 
0.1%
37.8159759036 11
 
0.1%
37.6499050791 10
 
0.1%
37.3491998472 9
 
0.1%
37.6449473083 9
 
0.1%
37.6979036758 9
 
0.1%
Other values (5592) 9763
97.6%
(Missing) 85
 
0.9%
ValueCountFrequency (%)
36.9357792327 6
0.1%
36.9385895346 2
 
< 0.1%
36.938720379 3
< 0.1%
36.9388029302 2
 
< 0.1%
36.9392777568 1
 
< 0.1%
36.9490886381 1
 
< 0.1%
36.9511883869 1
 
< 0.1%
36.9563046854 1
 
< 0.1%
36.9577536991 1
 
< 0.1%
36.9578672167 2
 
< 0.1%
ValueCountFrequency (%)
38.1091377255 1
 
< 0.1%
38.0975796466 5
0.1%
38.0945320935 1
 
< 0.1%
38.0898993569 1
 
< 0.1%
38.0893938632 2
 
< 0.1%
38.0893364592 1
 
< 0.1%
38.0769608039 1
 
< 0.1%
38.0683427258 2
 
< 0.1%
38.0679234619 1
 
< 0.1%
38.0669255768 4
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct5602
Distinct (%)56.5%
Missing85
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean127.03939
Minimum126.52556
Maximum127.77303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:22:53.865944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.52556
5-th percentile126.64296
Q1126.81386
median127.02403
Q3127.22207
95-th percentile127.49777
Maximum127.77303
Range1.2474735
Interquartile range (IQR)0.40820735

Descriptive statistics

Standard deviation0.25882521
Coefficient of variation (CV)0.0020373618
Kurtosis-0.57491566
Mean127.03939
Median Absolute Deviation (MAD)0.20289764
Skewness0.29747027
Sum1259595.6
Variance0.066990487
MonotonicityNot monotonic
2023-12-11T06:22:54.006443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.767192498 26
 
0.3%
127.1946802895 26
 
0.3%
126.9019008596 25
 
0.2%
126.7804711396 16
 
0.2%
126.8851106897 11
 
0.1%
126.8336198418 11
 
0.1%
126.7936807093 10
 
0.1%
126.9523635874 9
 
0.1%
127.3614538556 9
 
0.1%
126.7076634654 9
 
0.1%
Other values (5592) 9763
97.6%
(Missing) 85
 
0.9%
ValueCountFrequency (%)
126.5255574103 5
0.1%
126.5256474617 1
 
< 0.1%
126.5264481041 3
< 0.1%
126.531646159 1
 
< 0.1%
126.5365763029 2
 
< 0.1%
126.5384794086 1
 
< 0.1%
126.5405481825 2
 
< 0.1%
126.5432092679 1
 
< 0.1%
126.5432591078 2
 
< 0.1%
126.5452733136 1
 
< 0.1%
ValueCountFrequency (%)
127.7730308789 2
 
< 0.1%
127.7657858469 1
 
< 0.1%
127.7558229914 2
 
< 0.1%
127.7490742266 2
 
< 0.1%
127.7489168517 2
 
< 0.1%
127.7479740659 1
 
< 0.1%
127.7479402801 2
 
< 0.1%
127.7469879117 1
 
< 0.1%
127.7455049897 1
 
< 0.1%
127.7429048786 6
0.1%

Interactions

2023-12-11T06:22:46.686215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:44.471743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:45.216651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:45.683900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:46.193231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:46.805243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:44.558146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:45.303396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:45.776407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:46.303786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:46.915760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:44.668506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:45.397772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:45.882160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:46.389639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:47.026562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:44.788406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:45.486789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:45.982440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:46.483712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:47.128495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:45.100699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:45.574556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:46.077882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:46.580512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:22:54.099712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명평가일련번호평가유형구분평가점수평가등급업소위치인허가번호위도경도
시군명1.0000.4930.6730.3220.3340.7740.2790.9300.933
평가일련번호0.4931.0000.1870.2650.1790.2240.3620.2660.282
평가유형구분0.6730.1871.0000.2740.1060.0250.5470.3900.280
평가점수0.3220.2650.2741.0000.7870.1670.1610.2280.212
평가등급0.3340.1790.1060.7871.0000.0870.1650.1350.147
업소위치0.7740.2240.0250.1670.0871.0000.1700.3940.532
인허가번호0.2790.3620.5470.1610.1650.1701.0000.2330.185
위도0.9300.2660.3900.2280.1350.3940.2331.0000.682
경도0.9330.2820.2800.2120.1470.5320.1850.6821.000
2023-12-11T06:22:54.227236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가등급평가유형구분시군명업소위치
평가등급1.0000.1760.1780.082
평가유형구분0.1761.0000.5330.015
시군명0.1780.5331.0000.522
업소위치0.0820.0150.5221.000
2023-12-11T06:22:54.322130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가일련번호평가점수인허가번호위도경도시군명평가유형구분평가등급업소위치
평가일련번호1.0000.0970.210-0.037-0.0550.1960.3070.1080.135
평가점수0.0971.000-0.0910.026-0.0440.1190.1960.8020.101
인허가번호0.210-0.0911.000-0.022-0.0600.1010.3730.1000.102
위도-0.0370.026-0.0221.000-0.3140.6720.2980.0800.246
경도-0.055-0.044-0.060-0.3141.0000.6810.2130.0880.347
시군명0.1960.1190.1010.6720.6811.0000.5330.1780.522
평가유형구분0.3070.1960.3730.2980.2130.5331.0000.1760.015
평가등급0.1080.8020.1000.0800.0880.1780.1761.0000.082
업소위치0.1350.1010.1020.2460.3470.5220.0150.0821.000

Missing values

2023-12-11T06:22:47.284196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:22:47.504577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T06:22:47.686090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명평가일련번호평가계획일자평가유형구분평가일자평가점수평가등급업소위치인허가번호업체명대표자명점검불가여부소재지도로명주소소재지지번주소위도경도
3935광주시9060<NA><NA>2014-04-18156자율관리업소기타20120368172(주)대정에프엔디박환국<NA>경기도 광주시 오포읍 봉골길81번길 11-12경기도 광주시 오포읍 문형리 154-6번지37.351508127.20359
14603용인시33583<NA><NA>2016-07-26166자율관리업소도시20110347180오션나라김*두<NA>경기도 용인시 기흥구 신정로 203경기도 용인시 기흥구 신갈동 537-22번지37.288291127.100594
10352안성시46290<NA><NA>2018-11-15102일반관리업소<NA>20060360248착한마을사람들최*선<NA>경기도 안성시 대덕면 한사울길 125-50경기도 안성시 대덕면 삼한리 4번지37.062446127.281628
13819용인시49855<NA><NA>2019-09-0383중점관리업소<NA>20080347090텃밭한아름 영농조합법인이*엽<NA>경기도 용인시 처인구 남사면 원암로91번길 9경기도 용인시 처인구 남사면 원암리 137-5번지37.09058127.159404
16850이천시11515<NA><NA>2014-10-17141일반관리업소농어촌.산간20090358245주식회사 동일제빙서대원<NA>경기도 이천시 신둔면 경충대로 3035경기도 이천시 신둔면 수남리 90번지37.297265127.408271
7151부천시43327<NA><NA>2018-05-11145일반관리업소도시20160294304챔프커피하*경<NA>경기도 부천시 삼작로 205경기도 부천시 내동 274-2번지 2층일부37.520399126.784334
5374김포시43845<NA><NA>2018-08-09169자율관리업소농어촌.산간20130362521주식회사 용천차*자<NA>경기도 김포시 대곶면 대곶남로 53-34경기도 김포시 대곶면 대벽리 922-1번지37.606126126.575576
19352포천시35707<NA><NA>2016-10-10112일반관리업소기타20040372112고향유과김*서<NA>경기도 포천시 가산면 우금길 9경기도 포천시 가산면 우금리 299-3번지37.82419127.211476
11015안양시48446<NA><NA>2019-06-27114일반관리업소도시20180293292주식회사 둥구나무유*열<NA>경기도 안양시 만안구 전파로 64경기도 안양시 만안구 안양동 198-3번지 (지상2층 안양동)37.390009126.939731
7835수원시54909<NA><NA>2020-12-03120일반관리업소도시20160263538로시한*규<NA>경기도 수원시 영통구 웰빙타운로36번길 46-252경기도 수원시 영통구 이의동 1222-5번지 1층 이의동37.312058127.05438
시군명평가일련번호평가계획일자평가유형구분평가일자평가점수평가등급업소위치인허가번호업체명대표자명점검불가여부소재지도로명주소소재지지번주소위도경도
14487용인시224292017-03-20정기평가2017-03-20125일반관리업소농어촌.산간20130017138처인성주조이선재<NA>경기도 용인시 처인구 원삼면 미평로81번길 38-2경기도 용인시 처인구 원삼면 미평리 69-5번지 (경기도 용인시 처인구 원삼면 미평로81번길 38-2)37.181807127.326528
2480광명시39434<NA><NA>2017-09-12116일반관리업소<NA>20080304156(주)해가이*식<NA>경기도 광명시 원광명로37번길 35-1경기도 광명시 광명동 578번지37.463011126.853395
12787여주시51497<NA><NA>2019-12-13118일반관리업소농어촌.산간19990375251민속복떡집신*수<NA>경기도 여주시 여흥로11번길 56경기도 여주시 하동 317-3번지37.297996127.632126
11593양주시51546<NA><NA>2019-12-18126일반관리업소<NA>20180389902농업회사법인 주식회사 장수푸드연*희<NA>경기도 양주시 은현면 은현로56번길 97-23경기도 양주시 은현면 선암리 360-7번지 1층일부37.875274127.027017
13837용인시49009<NA><NA>2019-08-14118일반관리업소기타20140347187(주)제이다인구*자<NA>경기도 용인시 수지구 고기로525번길 30-1경기도 용인시 수지구 고기동 476-1번지 1층,2층 일부37.363814127.05142
19628포천시16558<NA><NA>2015-10-30144일반관리업소기타20100372445(주)매일건강최인호<NA>경기도 포천시 소흘읍 응골길 9경기도 포천시 소흘읍 초가팔리 163-1번지37.815254127.153029
3757광주시16078<NA><NA>2015-10-0645중점관리업소도시19700368001광주식품서은석<NA>경기도 광주시 역동로 77경기도 광주시 역동 139-8번지37.401612127.255732
10570안성시39988<NA><NA>2017-09-04134일반관리업소<NA>20120360198(주)송암푸드오*숙<NA>경기도 안성시 일죽면 소라태길 33경기도 안성시 일죽면 월정리 452-2번지37.090574127.456757
16314이천시43897<NA><NA>2018-08-28103일반관리업소농어촌.산간20120358476칠성농원이*열<NA>경기도 이천시 대월면 대월로373번길 250경기도 이천시 대월면 도리리 168-13번지37.196372127.48729
948고양시44494<NA><NA>2018-07-06176자율관리업소도시20150320390(주)쵸코스페이스 F1최*일<NA>경기도 고양시 일산동구 하늘마을로 170경기도 고양시 일산동구 중산동 1681번지 (대방트리플라온 비즈니스타워동 A-1301, A-1401~4호 중산동)37.679177126.778275

Duplicate rows

Most frequently occurring

시군명평가일련번호평가계획일자평가유형구분평가일자평가점수평가등급업소위치인허가번호업체명대표자명점검불가여부소재지도로명주소소재지지번주소위도경도# duplicates
11고양시24897<NA>정기평가2019-06-04109일반관리업소<NA>20080015264고양탁주합동제조장조성민<NA>경기도 고양시 덕양구 대주로 506경기도 고양시 덕양구 주교동 218-3(대주로 506)37.657605126.8266256
721안산시252912019-11-06정기평가2019-11-06127일반관리업소공단20180007752이곡주이명규<NA>경기도 안산시 단원구 별망로 336경기도 안산시 단원구 성곡동 615-2번지 2층 ((주)경진텍 1동)37.306725126.7622736
943여주시248412019-06-18정기평가2019-06-18-3<NA><NA>20160007214농업회사법인 주식회사 시월조용성Y경기도 여주시 흥천면 효자로 164경기도 여주시 흥천면 효지리 376-16번지37.333292127.5406986
1028용인시251132019-09-23정기평가2019-09-23153자율관리업소농어촌.산간20130017093정수와인권용완<NA>경기도 용인시 처인구 양지면 한터로864번길 45-22경기도 용인시 처인구 양지면 정수리 123-1 7/1(경기도 용인시 처인구 양지면 한터로864번길 45-22)37.265603127.2953656
1153의왕시247312019-05-22정기평가2019-05-22105일반관리업소도시20150006107주식회사 슈발바하최낙관<NA>경기도 의왕시 이미로 40경기도 의왕시 포일동 653번지 인덕원IT밸리 D동 308호37.400945126.9908316
355김포시240442019-03-25정기평가2019-03-19109일반관리업소농어촌.산간20130017042김포파주인삼농업협동조합경기서부인삼유통센터조재열<NA><NA>경기도 김포시 대곶면 대명리 391(경기도 김포시 대곶면 대명항로 518) 가동, 나동<NA><NA>5
451남양주시25064<NA>정기평가2019-09-09118일반관리업소<NA>20140015160오비맥주 주식회사브르노 카레이라 코센티노<NA>경기도 남양주시 화도읍 폭포로 361-1경기도 남양주시 화도읍 창현리 23-16번지37.634119127.3234615
579성남시249652019-07-09정기평가2019-07-09120일반관리업소도시20180006881느린마을양조장앤푸드(분당야탑점)송윤석<NA>경기도 성남시 분당구 야탑로105번길 18경기도 성남시 분당구 야탑동 371번지 2층37.411364127.1306565
716안산시246712019-04-22정기평가2019-04-22109일반관리업소<NA>20130017068안산양조장김현태<NA>경기도 안산시 상록구 동막길 70-1경기도 안산시 상록구 장상동 329번지37.349973126.8789365
718안산시25063<NA><NA>2019-07-10124일반관리업소공단20080311613광동케미칼(주)김준식<NA>경기도 안산시 단원구 번영2로안길 35경기도 안산시 단원구 성곡동 660-2번지 시화공단4다 101-237.327669126.7390315