Overview

Dataset statistics

Number of variables33
Number of observations1680
Missing cells18995
Missing cells (%)34.3%
Duplicate rows3
Duplicate rows (%)0.2%
Total size in memory467.7 KiB
Average record size in memory285.1 B

Variable types

Categorical13
Text5
DateTime2
Unsupported6
Numeric6
Boolean1

Alerts

다중이용업소여부 has constant value ""Constant
Dataset has 3 (0.2%) duplicate rowsDuplicates
영업상태구분코드 is highly imbalanced (56.8%)Imbalance
위생업태명 is highly imbalanced (93.0%)Imbalance
공장사무직종업원수 is highly imbalanced (65.4%)Imbalance
공장판매직종업원수 is highly imbalanced (65.4%)Imbalance
월세금액 is highly imbalanced (66.4%)Imbalance
인허가취소일자 has 1680 (100.0%) missing valuesMissing
폐업일자 has 908 (54.0%) missing valuesMissing
소재지시설전화번호 has 1549 (92.2%) missing valuesMissing
소재지면적정보 has 1486 (88.5%) missing valuesMissing
도로명우편번호 has 1455 (86.6%) missing valuesMissing
소재지도로명주소 has 82 (4.9%) missing valuesMissing
WGS84위도 has 246 (14.6%) missing valuesMissing
WGS84경도 has 246 (14.6%) missing valuesMissing
X좌표값 has 1456 (86.7%) missing valuesMissing
Y좌표값 has 1456 (86.7%) missing valuesMissing
영업장주변구분명 has 1680 (100.0%) missing valuesMissing
등급구분명 has 1680 (100.0%) missing valuesMissing
시설총규모 has 1680 (100.0%) missing valuesMissing
전통업소지정번호 has 1680 (100.0%) missing valuesMissing
전통업소음식 has 1680 (100.0%) missing valuesMissing
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적정보 has 20 (1.2%) zerosZeros

Reproduction

Analysis started2023-12-10 22:02:19.707833
Analysis finished2023-12-10 22:02:20.838289
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct31
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
용인시
150 
성남시
120 
남양주시
116 
하남시
 
99
수원시
 
91
Other values (26)
1104 

Length

Max length4
Median length3
Mean length3.0833333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가평군
2nd row가평군
3rd row가평군
4th row가평군
5th row가평군

Common Values

ValueCountFrequency (%)
용인시 150
 
8.9%
성남시 120
 
7.1%
남양주시 116
 
6.9%
하남시 99
 
5.9%
수원시 91
 
5.4%
안산시 80
 
4.8%
광주시 79
 
4.7%
연천군 73
 
4.3%
안양시 66
 
3.9%
화성시 65
 
3.9%
Other values (21) 741
44.1%

Length

2023-12-11T07:02:20.935143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용인시 150
 
8.9%
성남시 120
 
7.1%
남양주시 116
 
6.9%
하남시 99
 
5.9%
수원시 91
 
5.4%
안산시 80
 
4.8%
광주시 79
 
4.7%
연천군 73
 
4.3%
안양시 66
 
3.9%
화성시 65
 
3.9%
Other values (21) 741
44.1%

사업장명
Text

Distinct1434
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
2023-12-11T07:02:21.200496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length7.2059524
Min length2

Characters and Unicode

Total characters12106
Distinct characters437
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1247 ?
Unique (%)74.2%

Sample

1st row(주)태영지엘에스
2nd row(주)국제냉동운수
3rd row(주)사람과물류
4th row(주)좋은식품들
5th row유명케터링
ValueCountFrequency (%)
주식회사 101
 
5.5%
주 15
 
0.8%
개별화물 13
 
0.7%
주)이안지엘에스 6
 
0.3%
개별용달 5
 
0.3%
농업회사법인 5
 
0.3%
주)스카이물류 5
 
0.3%
미서운수 5
 
0.3%
주)대일운수 4
 
0.2%
주)조은냉장 4
 
0.2%
Other values (1463) 1690
91.2%
2023-12-11T07:02:21.569653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1077
 
8.9%
) 928
 
7.7%
( 918
 
7.6%
스 393
 
3.2%
물 314
 
2.6%
운 300
 
2.5%
수 254
 
2.1%
류 254
 
2.1%
식 252
 
2.1%
지 241
 
2.0%
Other values (427) 7175
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9930
82.0%
Close Punctuation 928
 
7.7%
Open Punctuation 918
 
7.6%
Space Separator 173
 
1.4%
Uppercase Letter 69
 
0.6%
Decimal Number 56
 
0.5%
Other Punctuation 22
 
0.2%
Lowercase Letter 9
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1077
 
10.8%
스 393
 
4.0%
물 314
 
3.2%
운 300
 
3.0%
수 254
 
2.6%
류 254
 
2.6%
식 252
 
2.5%
지 241
 
2.4%
사 227
 
2.3%
이 202
 
2.0%
Other values (388) 6416
64.6%
Uppercase Letter
ValueCountFrequency (%)
S 15
21.7%
F 15
21.7%
O 6
 
8.7%
B 6
 
8.7%
C 4
 
5.8%
K 4
 
5.8%
M 4
 
5.8%
D 4
 
5.8%
L 3
 
4.3%
W 3
 
4.3%
Other values (4) 5
 
7.2%
Decimal Number
ValueCountFrequency (%)
9 12
21.4%
1 8
14.3%
8 7
12.5%
0 7
12.5%
4 6
10.7%
3 5
8.9%
5 4
 
7.1%
2 4
 
7.1%
6 2
 
3.6%
7 1
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
l 2
22.2%
n 1
11.1%
f 1
11.1%
r 1
11.1%
i 1
11.1%
b 1
11.1%
Other Punctuation
ValueCountFrequency (%)
. 12
54.5%
& 8
36.4%
, 1
 
4.5%
/ 1
 
4.5%
Close Punctuation
ValueCountFrequency (%)
) 928
100.0%
Open Punctuation
ValueCountFrequency (%)
( 918
100.0%
Space Separator
ValueCountFrequency (%)
173
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9930
82.0%
Common 2098
 
17.3%
Latin 78
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1077
 
10.8%
스 393
 
4.0%
물 314
 
3.2%
운 300
 
3.0%
수 254
 
2.6%
류 254
 
2.6%
식 252
 
2.5%
지 241
 
2.4%
사 227
 
2.3%
이 202
 
2.0%
Other values (388) 6416
64.6%
Latin
ValueCountFrequency (%)
S 15
19.2%
F 15
19.2%
O 6
 
7.7%
B 6
 
7.7%
C 4
 
5.1%
K 4
 
5.1%
M 4
 
5.1%
D 4
 
5.1%
L 3
 
3.8%
W 3
 
3.8%
Other values (11) 14
17.9%
Common
ValueCountFrequency (%)
) 928
44.2%
( 918
43.8%
173
 
8.2%
9 12
 
0.6%
. 12
 
0.6%
1 8
 
0.4%
& 8
 
0.4%
8 7
 
0.3%
0 7
 
0.3%
4 6
 
0.3%
Other values (8) 19
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9930
82.0%
ASCII 2176
 
18.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1077
 
10.8%
스 393
 
4.0%
물 314
 
3.2%
운 300
 
3.0%
수 254
 
2.6%
류 254
 
2.6%
식 252
 
2.5%
지 241
 
2.4%
사 227
 
2.3%
이 202
 
2.0%
Other values (388) 6416
64.6%
ASCII
ValueCountFrequency (%)
) 928
42.6%
( 918
42.2%
173
 
8.0%
S 15
 
0.7%
F 15
 
0.7%
9 12
 
0.6%
. 12
 
0.6%
1 8
 
0.4%
& 8
 
0.4%
8 7
 
0.3%
Other values (29) 80
 
3.7%

인허가일자
Date

Distinct1195
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
Minimum1977-09-09 00:00:00
Maximum2023-11-30 00:00:00
2023-12-11T07:02:21.694771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:02:21.833286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1680
Missing (%)100.0%
Memory size14.9 KiB

영업상태구분코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1451 
1
172 
2
 
57

Length

Max length4
Median length4
Mean length3.5910714
Min length1

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> 1451
86.4%
1 172
 
10.2%
2 57
 
3.4%

Length

2023-12-11T07:02:21.956939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:22.074873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1451
86.4%
1 172
 
10.2%
2 57
 
3.4%

영업상태명
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
운영중
736 
폐업 등
715 
영업
172 
폐업
 
57

Length

Max length4
Median length3
Mean length3.2892857
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row운영중
2nd row운영중
3rd row운영중
4th row폐업 등
5th row폐업 등

Common Values

ValueCountFrequency (%)
운영중 736
43.8%
폐업 등 715
42.6%
영업 172
 
10.2%
폐업 57
 
3.4%

Length

2023-12-11T07:02:22.190633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:22.337255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 772
32.2%
운영중 736
30.7%
등 715
29.9%
영업 172
 
7.2%

폐업일자
Date

MISSING 

Distinct636
Distinct (%)82.4%
Missing908
Missing (%)54.0%
Memory size13.3 KiB
Minimum2000-05-01 00:00:00
Maximum2023-12-04 00:00:00
2023-12-11T07:02:22.462737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:02:22.582516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지시설전화번호
Text

MISSING 

Distinct119
Distinct (%)90.8%
Missing1549
Missing (%)92.2%
Memory size13.3 KiB
2023-12-11T07:02:22.883688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.320611
Min length7

Characters and Unicode

Total characters1483
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

Unique111 ?
Unique (%)84.7%

Sample

1st row15220312
2nd row031 4235210
3rd row031 762 2990
4th row032 763 1135
5th row031 903 9724
ValueCountFrequency (%)
031 76
24.2%
02 22
 
7.0%
575 7
 
2.2%
0141 6
 
1.9%
032 5
 
1.6%
070 4
 
1.3%
235 3
 
1.0%
378 3
 
1.0%
03180540855 2
 
0.6%
795 2
 
0.6%
Other values (171) 184
58.6%
2023-12-11T07:02:23.330347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 224
15.1%
199
13.4%
3 188
12.7%
1 171
11.5%
2 124
8.4%
5 116
7.8%
8 114
7.7%
7 111
7.5%
4 94
6.3%
6 82
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1284
86.6%
Space Separator 199
 
13.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 224
17.4%
3 188
14.6%
1 171
13.3%
2 124
9.7%
5 116
9.0%
8 114
8.9%
7 111
8.6%
4 94
7.3%
6 82
 
6.4%
9 60
 
4.7%
Space Separator
ValueCountFrequency (%)
199
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1483
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 224
15.1%
199
13.4%
3 188
12.7%
1 171
11.5%
2 124
8.4%
5 116
7.8%
8 114
7.7%
7 111
7.5%
4 94
6.3%
6 82
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1483
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 224
15.1%
199
13.4%
3 188
12.7%
1 171
11.5%
2 124
8.4%
5 116
7.8%
8 114
7.7%
7 111
7.5%
4 94
6.3%
6 82
 
5.5%

소재지면적정보
Real number (ℝ)

MISSING  ZEROS 

Distinct141
Distinct (%)72.7%
Missing1486
Missing (%)88.5%
Infinite0
Infinite (%)0.0%
Mean243.28964
Minimum0
Maximum29560.05
Zeros20
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2023-12-11T07:02:23.523160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110
median33.31
Q388.135
95-th percentile268.911
Maximum29560.05
Range29560.05
Interquartile range (IQR)78.135

Descriptive statistics

Standard deviation2139.1301
Coefficient of variation (CV)8.7925244
Kurtosis185.56699
Mean243.28964
Median Absolute Deviation (MAD)28.06
Skewness13.504784
Sum47198.19
Variance4575877.5
MonotonicityNot monotonic
2023-12-11T07:02:23.672020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 20
 
1.2%
16.5 6
 
0.4%
3.3 6
 
0.4%
10.0 6
 
0.4%
33.0 4
 
0.2%
15.0 3
 
0.2%
9.9 3
 
0.2%
6.6 3
 
0.2%
42.9 2
 
0.1%
38.66 2
 
0.1%
Other values (131) 139
 
8.3%
(Missing) 1486
88.5%
ValueCountFrequency (%)
0.0 20
1.2%
1.2 1
 
0.1%
1.5 1
 
0.1%
2.2 1
 
0.1%
3.3 6
 
0.4%
3.6 1
 
0.1%
4.0 1
 
0.1%
4.8 1
 
0.1%
5.0 1
 
0.1%
5.5 1
 
0.1%
ValueCountFrequency (%)
29560.05 1
0.1%
3961.2 1
0.1%
1626.0 1
0.1%
915.96 1
0.1%
410.99 1
0.1%
383.58 1
0.1%
297.2 1
0.1%
293.0 1
0.1%
276.65 1
0.1%
272.46 1
0.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)84.9%
Missing1455
Missing (%)86.6%
Infinite0
Infinite (%)0.0%
Mean14777.2
Minimum10065
Maximum18599
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2023-12-11T07:02:23.802045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10065
5-th percentile10562.2
Q112940
median14626
Q316965
95-th percentile18264.6
Maximum18599
Range8534
Interquartile range (IQR)4025

Descriptive statistics

Standard deviation2401.5798
Coefficient of variation (CV)0.16251927
Kurtosis-1.0695723
Mean14777.2
Median Absolute Deviation (MAD)1936
Skewness-0.20135171
Sum3324870
Variance5767585.6
MonotonicityNot monotonic
2023-12-11T07:02:24.201317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13951 4
 
0.2%
13494 4
 
0.2%
13616 3
 
0.2%
12986 3
 
0.2%
16642 3
 
0.2%
16300 2
 
0.1%
11130 2
 
0.1%
12269 2
 
0.1%
14548 2
 
0.1%
13646 2
 
0.1%
Other values (181) 198
 
11.8%
(Missing) 1455
86.6%
ValueCountFrequency (%)
10065 1
0.1%
10068 1
0.1%
10120 1
0.1%
10124 1
0.1%
10243 1
0.1%
10252 1
0.1%
10364 1
0.1%
10383 1
0.1%
10402 1
0.1%
10449 2
0.1%
ValueCountFrequency (%)
18599 1
0.1%
18582 1
0.1%
18522 1
0.1%
18484 1
0.1%
18469 1
0.1%
18455 2
0.1%
18387 1
0.1%
18332 1
0.1%
18326 2
0.1%
18293 1
0.1%

소재지도로명주소
Text

MISSING 

Distinct1212
Distinct (%)75.8%
Missing82
Missing (%)4.9%
Memory size13.3 KiB
2023-12-11T07:02:24.532754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length48
Mean length28.334168
Min length13

Characters and Unicode

Total characters45278
Distinct characters435
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1024 ?
Unique (%)64.1%

Sample

1st row경기도 가평군 조종면 조종희망로 *, 태영빌딩 *층
2nd row경기도 가평군 가평읍 태봉두밀로 *-**
3rd row경기도 가평군 북면 백둔로 ***
4th row경기도 가평군 설악면 어비산길 ***-*
5th row경기도 가평군 가평읍 불기산길 **-*
ValueCountFrequency (%)
1617
 
16.6%
경기도 1598
 
16.4%
층 429
 
4.4%
호 309
 
3.2%
용인시 142
 
1.5%
남양주시 115
 
1.2%
성남시 114
 
1.2%
하남시 94
 
1.0%
수원시 86
 
0.9%
안산시 78
 
0.8%
Other values (1637) 5145
52.9%
2023-12-11T07:02:25.013657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8139
18.0%
* 7761
17.1%
기 1714
 
3.8%
도 1706
 
3.8%
경 1648
 
3.6%
시 1612
 
3.6%
로 1427
 
3.2%
동 1270
 
2.8%
, 1011
 
2.2%
( 984
 
2.2%
Other values (425) 18006
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25909
57.2%
Other Punctuation 8778
 
19.4%
Space Separator 8139
 
18.0%
Open Punctuation 984
 
2.2%
Close Punctuation 984
 
2.2%
Dash Punctuation 373
 
0.8%
Uppercase Letter 110
 
0.2%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1714
 
6.6%
도 1706
 
6.6%
경 1648
 
6.4%
시 1612
 
6.2%
로 1427
 
5.5%
동 1270
 
4.9%
길 776
 
3.0%
구 649
 
2.5%
번 589
 
2.3%
층 550
 
2.1%
Other values (396) 13968
53.9%
Uppercase Letter
ValueCountFrequency (%)
A 35
31.8%
B 25
22.7%
I 13
 
11.8%
T 8
 
7.3%
C 5
 
4.5%
L 3
 
2.7%
E 3
 
2.7%
S 2
 
1.8%
U 2
 
1.8%
O 2
 
1.8%
Other values (10) 12
 
10.9%
Other Punctuation
ValueCountFrequency (%)
* 7761
88.4%
, 1011
 
11.5%
. 5
 
0.1%
@ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
8139
100.0%
Open Punctuation
ValueCountFrequency (%)
( 984
100.0%
Close Punctuation
ValueCountFrequency (%)
) 984
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 373
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25909
57.2%
Common 19258
42.5%
Latin 111
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1714
 
6.6%
도 1706
 
6.6%
경 1648
 
6.4%
시 1612
 
6.2%
로 1427
 
5.5%
동 1270
 
4.9%
길 776
 
3.0%
구 649
 
2.5%
번 589
 
2.3%
층 550
 
2.1%
Other values (396) 13968
53.9%
Latin
ValueCountFrequency (%)
A 35
31.5%
B 25
22.5%
I 13
 
11.7%
T 8
 
7.2%
C 5
 
4.5%
L 3
 
2.7%
E 3
 
2.7%
S 2
 
1.8%
U 2
 
1.8%
O 2
 
1.8%
Other values (11) 13
 
11.7%
Common
ValueCountFrequency (%)
8139
42.3%
* 7761
40.3%
, 1011
 
5.2%
( 984
 
5.1%
) 984
 
5.1%
- 373
 
1.9%
. 5
 
< 0.1%
@ 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25909
57.2%
ASCII 19369
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8139
42.0%
* 7761
40.1%
, 1011
 
5.2%
( 984
 
5.1%
) 984
 
5.1%
- 373
 
1.9%
A 35
 
0.2%
B 25
 
0.1%
I 13
 
0.1%
T 8
 
< 0.1%
Other values (19) 36
 
0.2%
Hangul
ValueCountFrequency (%)
기 1714
 
6.6%
도 1706
 
6.6%
경 1648
 
6.4%
시 1612
 
6.2%
로 1427
 
5.5%
동 1270
 
4.9%
길 776
 
3.0%
구 649
 
2.5%
번 589
 
2.3%
층 550
 
2.1%
Other values (396) 13968
53.9%

소재지지번주소
Text

Distinct1304
Distinct (%)77.7%
Missing1
Missing (%)0.1%
Memory size13.3 KiB
2023-12-11T07:02:25.350022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length42
Mean length25.852889
Min length13

Characters and Unicode

Total characters43407
Distinct characters395
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1131 ?
Unique (%)67.4%

Sample

1st row경기도 가평군 조종면 현리 ***-*번지
2nd row경기도 가평군 가평읍 상색리 ***-*번지
3rd row경기도 가평군 가평읍 상색리 ***-**번지
4th row경기도 가평군 북면 백둔리 ***번지
5th row경기도 가평군 설악면 가일리 **-*번지
ValueCountFrequency (%)
경기도 1679
 
18.0%
번지 1451
 
15.5%
층 382
 
4.1%
호 271
 
2.9%
250
 
2.7%
용인시 150
 
1.6%
성남시 120
 
1.3%
남양주시 116
 
1.2%
하남시 99
 
1.1%
수원시 91
 
1.0%
Other values (1105) 4736
50.7%
2023-12-11T07:02:25.789912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8418
19.4%
7862
18.1%
도 1812
 
4.2%
기 1769
 
4.1%
경 1684
 
3.9%
시 1659
 
3.8%
지 1657
 
3.8%
동 1467
 
3.4%
번 1452
 
3.3%
- 1300
 
3.0%
Other values (385) 14327
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25417
58.6%
Other Punctuation 8460
 
19.5%
Space Separator 7862
 
18.1%
Dash Punctuation 1300
 
3.0%
Open Punctuation 134
 
0.3%
Close Punctuation 132
 
0.3%
Uppercase Letter 100
 
0.2%
Lowercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 1812
 
7.1%
기 1769
 
7.0%
경 1684
 
6.6%
시 1659
 
6.5%
지 1657
 
6.5%
동 1467
 
5.8%
번 1452
 
5.7%
구 640
 
2.5%
리 610
 
2.4%
층 483
 
1.9%
Other values (358) 12184
47.9%
Uppercase Letter
ValueCountFrequency (%)
A 31
31.0%
B 25
25.0%
I 13
13.0%
T 9
 
9.0%
C 4
 
4.0%
E 2
 
2.0%
L 2
 
2.0%
S 2
 
2.0%
U 2
 
2.0%
K 2
 
2.0%
Other values (8) 8
 
8.0%
Other Punctuation
ValueCountFrequency (%)
* 8418
99.5%
, 33
 
0.4%
. 9
 
0.1%
Space Separator
ValueCountFrequency (%)
7862
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1300
100.0%
Open Punctuation
ValueCountFrequency (%)
( 134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 132
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25417
58.6%
Common 17889
41.2%
Latin 101
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 1812
 
7.1%
기 1769
 
7.0%
경 1684
 
6.6%
시 1659
 
6.5%
지 1657
 
6.5%
동 1467
 
5.8%
번 1452
 
5.7%
구 640
 
2.5%
리 610
 
2.4%
층 483
 
1.9%
Other values (358) 12184
47.9%
Latin
ValueCountFrequency (%)
A 31
30.7%
B 25
24.8%
I 13
12.9%
T 9
 
8.9%
C 4
 
4.0%
E 2
 
2.0%
L 2
 
2.0%
S 2
 
2.0%
U 2
 
2.0%
K 2
 
2.0%
Other values (9) 9
 
8.9%
Common
ValueCountFrequency (%)
* 8418
47.1%
7862
43.9%
- 1300
 
7.3%
( 134
 
0.7%
) 132
 
0.7%
, 33
 
0.2%
. 9
 
0.1%
~ 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25417
58.6%
ASCII 17990
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8418
46.8%
7862
43.7%
- 1300
 
7.2%
( 134
 
0.7%
) 132
 
0.7%
, 33
 
0.2%
A 31
 
0.2%
B 25
 
0.1%
I 13
 
0.1%
. 9
 
0.1%
Other values (17) 33
 
0.2%
Hangul
ValueCountFrequency (%)
도 1812
 
7.1%
기 1769
 
7.0%
경 1684
 
6.6%
시 1659
 
6.5%
지 1657
 
6.5%
동 1467
 
5.8%
번 1452
 
5.7%
구 640
 
2.5%
리 610
 
2.4%
층 483
 
1.9%
Other values (358) 12184
47.9%

소재지우편번호
Text

Distinct852
Distinct (%)51.2%
Missing16
Missing (%)1.0%
Memory size13.3 KiB
2023-12-11T07:02:26.082751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0907452
Min length5

Characters and Unicode

Total characters10135
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

Unique539 ?
Unique (%)32.4%

Sample

1st row12437
2nd row477806
3rd row477806
4th row477842
5th row477851
ValueCountFrequency (%)
472913 74
 
4.4%
486803 32
 
1.9%
463824 16
 
1.0%
487881 15
 
0.9%
471829 13
 
0.8%
465816 13
 
0.8%
465220 13
 
0.8%
446904 10
 
0.6%
435835 10
 
0.6%
469851 10
 
0.6%
Other values (842) 1458
87.6%
2023-12-11T07:02:26.514909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2367
23.4%
8 1255
12.4%
1 991
9.8%
0 968
9.6%
2 891
 
8.8%
6 866
 
8.5%
3 776
 
7.7%
5 716
 
7.1%
9 582
 
5.7%
7 510
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9922
97.9%
Dash Punctuation 213
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 2367
23.9%
8 1255
12.6%
1 991
10.0%
0 968
9.8%
2 891
 
9.0%
6 866
 
8.7%
3 776
 
7.8%
5 716
 
7.2%
9 582
 
5.9%
7 510
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 213
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10135
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 2367
23.4%
8 1255
12.4%
1 991
9.8%
0 968
9.6%
2 891
 
8.8%
6 866
 
8.5%
3 776
 
7.7%
5 716
 
7.1%
9 582
 
5.7%
7 510
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2367
23.4%
8 1255
12.4%
1 991
9.8%
0 968
9.6%
2 891
 
8.8%
6 866
 
8.5%
3 776
 
7.7%
5 716
 
7.1%
9 582
 
5.7%
7 510
 
5.0%

WGS84위도
Real number (ℝ)

MISSING 

Distinct1028
Distinct (%)71.7%
Missing246
Missing (%)14.6%
Infinite0
Infinite (%)0.0%
Mean37.440855
Minimum36.937795
Maximum38.186774
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2023-12-11T07:02:26.661567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.937795
5-th percentile37.055816
Q137.276221
median37.398868
Q337.610332
95-th percentile37.979708
Maximum38.186774
Range1.2489796
Interquartile range (IQR)0.33411055

Descriptive statistics

Standard deviation0.25185378
Coefficient of variation (CV)0.0067267102
Kurtosis0.52281438
Mean37.440855
Median Absolute Deviation (MAD)0.14211958
Skewness0.73288208
Sum53690.187
Variance0.063430327
MonotonicityNot monotonic
2023-12-11T07:02:26.794406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6141999129 78
 
4.6%
37.3851007981 16
 
1.0%
37.9696176208 10
 
0.6%
37.3003737575 10
 
0.6%
37.3303008024 9
 
0.5%
38.0975323133 9
 
0.5%
37.6103315074 8
 
0.5%
38.1841147997 7
 
0.4%
38.0928321665 7
 
0.4%
37.4707831388 7
 
0.4%
Other values (1018) 1273
75.8%
(Missing) 246
 
14.6%
ValueCountFrequency (%)
36.9377948562 1
0.1%
36.9563185772 1
0.1%
36.9576165524 1
0.1%
36.9626498313 1
0.1%
36.9637259612 1
0.1%
36.9652812217 1
0.1%
36.9664417128 1
0.1%
36.9708236626 1
0.1%
36.9710849938 1
0.1%
36.9744739968 1
0.1%
ValueCountFrequency (%)
38.1867744123 1
 
0.1%
38.1841147997 7
0.4%
38.1623698505 2
 
0.1%
38.1466797395 1
 
0.1%
38.1235639079 5
0.3%
38.104152064 1
 
0.1%
38.1018613247 1
 
0.1%
38.0998807246 3
 
0.2%
38.0975323133 9
0.5%
38.0966264721 1
 
0.1%

WGS84경도
Real number (ℝ)

MISSING 

Distinct1028
Distinct (%)71.7%
Missing246
Missing (%)14.6%
Infinite0
Infinite (%)0.0%
Mean127.07978
Minimum126.55406
Maximum127.6887
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2023-12-11T07:02:26.935611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55406
5-th percentile126.76289
Q1126.94581
median127.10016
Q3127.18469
95-th percentile127.46564
Maximum127.6887
Range1.1346438
Interquartile range (IQR)0.23888001

Descriptive statistics

Standard deviation0.20420468
Coefficient of variation (CV)0.0016069015
Kurtosis0.599024
Mean127.07978
Median Absolute Deviation (MAD)0.11803544
Skewness0.38994564
Sum182232.4
Variance0.041699552
MonotonicityNot monotonic
2023-12-11T07:02:27.067617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1490074492 78
 
4.6%
127.1227076252 16
 
1.0%
127.2276669521 10
 
0.6%
127.686843709 10
 
0.6%
126.9357157649 9
 
0.5%
127.0744579996 9
 
0.5%
127.1454453107 8
 
0.5%
127.1157576154 7
 
0.4%
127.0732079839 7
 
0.4%
127.3150287591 7
 
0.4%
Other values (1018) 1273
75.8%
(Missing) 246
 
14.6%
ValueCountFrequency (%)
126.5540586718 1
 
0.1%
126.5543720479 1
 
0.1%
126.5578982848 1
 
0.1%
126.5643424968 1
 
0.1%
126.5721371239 3
0.2%
126.597497054 1
 
0.1%
126.6259139525 1
 
0.1%
126.6354372746 2
0.1%
126.6361545321 1
 
0.1%
126.636695681 2
0.1%
ValueCountFrequency (%)
127.6887024994 1
 
0.1%
127.686843709 10
0.6%
127.6863429449 1
 
0.1%
127.6706945499 1
 
0.1%
127.6702674323 1
 
0.1%
127.665257989 1
 
0.1%
127.6622400312 1
 
0.1%
127.6618110691 1
 
0.1%
127.6524818007 1
 
0.1%
127.6417304677 1
 
0.1%

업태구분명정보
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1451 
식품운반업
229 

Length

Max length5
Median length4
Mean length4.1363095
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> 1451
86.4%
식품운반업 229
 
13.6%

Length

2023-12-11T07:02:27.187093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:27.283772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1451
86.4%
식품운반업 229
 
13.6%

X좌표값
Real number (ℝ)

MISSING 

Distinct203
Distinct (%)90.6%
Missing1456
Missing (%)86.7%
Infinite0
Infinite (%)0.0%
Mean204138.06
Minimum167330.88
Maximum261121.78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2023-12-11T07:02:27.380199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum167330.88
5-th percentile179269.3
Q1189503.76
median203106.92
Q3213942.9
95-th percentile235485.23
Maximum261121.78
Range93790.898
Interquartile range (IQR)24439.146

Descriptive statistics

Standard deviation18517.579
Coefficient of variation (CV)0.090711059
Kurtosis0.97229183
Mean204138.06
Median Absolute Deviation (MAD)11031.891
Skewness0.80427556
Sum45726925
Variance3.4290074 × 108
MonotonicityNot monotonic
2023-12-11T07:02:27.508353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209374.879569806 4
 
0.2%
197721.024967918 4
 
0.2%
197976.786239943 3
 
0.2%
209268.321106193 3
 
0.2%
255873.601027736 2
 
0.1%
200034.179829026 2
 
0.1%
195990.03651047 2
 
0.1%
227790.349506137 2
 
0.1%
183096.302229304 2
 
0.1%
179871.92387426 2
 
0.1%
Other values (193) 198
 
11.8%
(Missing) 1456
86.7%
ValueCountFrequency (%)
167330.881853243 1
0.1%
168471.749240332 1
0.1%
175358.007571786 1
0.1%
175751.992022502 1
0.1%
177241.744343871 1
0.1%
177948.295176884 1
0.1%
177982.753747441 1
0.1%
178038.654941912 1
0.1%
178292.039499578 1
0.1%
178347.563416869 1
0.1%
ValueCountFrequency (%)
261121.779485652 1
0.1%
260829.225755134 1
0.1%
260782.023377459 1
0.1%
259336.359487112 1
0.1%
255873.601027736 2
0.1%
255012.336125529 1
0.1%
252497.093181621 1
0.1%
250540.088601089 1
0.1%
247076.64108745 1
0.1%
240608.331868689 1
0.1%

Y좌표값
Real number (ℝ)

MISSING 

Distinct203
Distinct (%)90.6%
Missing1456
Missing (%)86.7%
Infinite0
Infinite (%)0.0%
Mean432415.93
Minimum381828.97
Maximum520078.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2023-12-11T07:02:27.619156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum381828.97
5-th percentile397401.22
Q1417095.35
median427643.07
Q3444708.14
95-th percentile480904.85
Maximum520078.25
Range138249.28
Interquartile range (IQR)27612.798

Descriptive statistics

Standard deviation25385.39
Coefficient of variation (CV)0.058705955
Kurtosis1.1494733
Mean432415.93
Median Absolute Deviation (MAD)13398.323
Skewness0.87730804
Sum96861169
Variance6.4441805 × 108
MonotonicityNot monotonic
2023-12-11T07:02:27.740147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
433334.937936425 4
 
0.2%
433149.964036601 4
 
0.2%
415511.760672979 3
 
0.2%
427643.0746251 3
 
0.2%
408396.926733415 2
 
0.1%
422678.949290635 2
 
0.1%
426030.544674384 2
 
0.1%
441010.567924203 2
 
0.1%
429699.494640402 2
 
0.1%
444333.380509177 2
 
0.1%
Other values (193) 198
 
11.8%
(Missing) 1456
86.7%
ValueCountFrequency (%)
381828.9673366 1
0.1%
383706.991013814 1
0.1%
385562.215626508 1
0.1%
386818.88927666 1
0.1%
387830.462917531 1
0.1%
388081.018678084 1
0.1%
389208.324806486 1
0.1%
392686.783065917 1
0.1%
393418.387999999 1
0.1%
394871.532291568 1
0.1%
ValueCountFrequency (%)
520078.248602628 1
0.1%
511261.053543503 1
0.1%
510523.085220783 1
0.1%
510003.242531114 1
0.1%
500859.323049379 1
0.1%
497348.622236687 1
0.1%
496338.770532326 1
0.1%
496323.590912896 1
0.1%
488926.417051091 1
0.1%
483788.771221043 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
식품운반업
1666 
<NA>
 
14

Length

Max length5
Median length5
Mean length4.9916667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row식품운반업
2nd row식품운반업
3rd row식품운반업
4th row식품운반업
5th row식품운반업

Common Values

ValueCountFrequency (%)
식품운반업 1666
99.2%
<NA> 14
 
0.8%

Length

2023-12-11T07:02:27.878746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:27.978313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 1666
99.2%
na 14
 
0.8%

남성종사자수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1483 
0
197 

Length

Max length4
Median length4
Mean length3.6482143
Min length1

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> 1483
88.3%
0 197
 
11.7%

Length

2023-12-11T07:02:28.108383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:28.211229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1483
88.3%
0 197
 
11.7%

여성종사자수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1483 
0
197 

Length

Max length4
Median length4
Mean length3.6482143
Min length1

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> 1483
88.3%
0 197
 
11.7%

Length

2023-12-11T07:02:28.312125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:28.406584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1483
88.3%
0 197
 
11.7%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1680
Missing (%)100.0%
Memory size14.9 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1680
Missing (%)100.0%
Memory size14.9 KiB

본사종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1470 
0
210 

Length

Max length4
Median length4
Mean length3.625
Min length1

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> 1470
87.5%
0 210
 
12.5%

Length

2023-12-11T07:02:28.504619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:28.594917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1470
87.5%
0 210
 
12.5%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1470 
0
209 
2
 
1

Length

Max length4
Median length4
Mean length3.625
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1470
87.5%
0 209
 
12.4%
2 1
 
0.1%

Length

2023-12-11T07:02:28.688707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:28.800891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1470
87.5%
0 209
 
12.4%
2 1
 
0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1470 
0
209 
1
 
1

Length

Max length4
Median length4
Mean length3.625
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1470
87.5%
0 209
 
12.4%
1 1
 
0.1%

Length

2023-12-11T07:02:28.909580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:29.004817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1470
87.5%
0 209
 
12.4%
1 1
 
0.1%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1470 
0
210 

Length

Max length4
Median length4
Mean length3.625
Min length1

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> 1470
87.5%
0 210
 
12.5%

Length

2023-12-11T07:02:29.130281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:29.228395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1470
87.5%
0 210
 
12.5%

보증금액
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1480 
0
200 

Length

Max length4
Median length4
Mean length3.6428571
Min length1

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> 1480
88.1%
0 200
 
11.9%

Length

2023-12-11T07:02:29.324688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:29.415868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1480
88.1%
0 200
 
11.9%

월세금액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1480 
0
199 
50000
 
1

Length

Max length5
Median length4
Mean length3.6452381
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1480
88.1%
0 199
 
11.8%
50000 1
 
0.1%

Length

2023-12-11T07:02:29.531388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:29.635751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1480
88.1%
0 199
 
11.8%
50000 1
 
0.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing14
Missing (%)0.8%
Memory size3.4 KiB
False
1666 
(Missing)
 
14
ValueCountFrequency (%)
False 1666
99.2%
(Missing) 14
 
0.8%
2023-12-11T07:02:29.711423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1680
Missing (%)100.0%
Memory size14.9 KiB

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1680
Missing (%)100.0%
Memory size14.9 KiB

전통업소음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1680
Missing (%)100.0%
Memory size14.9 KiB

Sample

시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수보증금액월세금액다중이용업소여부시설총규모전통업소지정번호전통업소음식
0가평군(주)태영지엘에스20171221<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 조종면 조종희망로 *, 태영빌딩 *층경기도 가평군 조종면 현리 ***-*번지1243737.818354127.34908<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
1가평군(주)국제냉동운수20070814<NA><NA>운영중<NA><NA><NA><NA><NA>경기도 가평군 가평읍 상색리 ***-*번지47780637.804487127.48555<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
2가평군(주)사람과물류20051027<NA><NA>운영중<NA><NA><NA><NA>경기도 가평군 가평읍 태봉두밀로 *-**경기도 가평군 가평읍 상색리 ***-**번지47780637.803983127.486664<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
3가평군(주)좋은식품들20090910<NA><NA>폐업 등20110127<NA><NA><NA>경기도 가평군 북면 백둔로 ***경기도 가평군 북면 백둔리 ***번지47784237.901328127.460371<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
4가평군유명케터링20040303<NA><NA>폐업 등20161117<NA><NA><NA>경기도 가평군 설악면 어비산길 ***-*경기도 가평군 설악면 가일리 **-*번지47785137.591728127.5105<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
5가평군강원농산유통20080513<NA><NA>폐업 등20120531<NA><NA><NA>경기도 가평군 가평읍 불기산길 **-*경기도 가평군 가평읍 상색리 ***번지47780637.798673127.477203<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
6가평군풍산해물유통20080131<NA><NA>폐업 등20120130<NA><NA><NA>경기도 가평군 가평읍 연인*길 **-*경기도 가평군 가평읍 읍내리 ***-**번지47780137.829608127.51217<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
7가평군동원단체급식푸드시스템20060425<NA><NA>폐업 등20100119<NA><NA><NA>경기도 가평군 가평읍 오리나무길 **경기도 가평군 가평읍 대곡리 ***-*번지47780437.824705127.514204<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
8고양시(주)우리로지텍2021-06-03<NA>1영업<NA><NA>35.710243경기도 고양시 일산서구 현중로 **, 탄현마을상가동 지층 **호 (탄현동)경기도 고양시 일산서구 탄현동 **** 탄현마을상가동 지층**호411-320<NA><NA>식품운반업179310.163694465988.692772식품운반업00<NA><NA>000000N<NA><NA><NA>
9고양시하늘물류주식회사2015-06-10<NA>1영업<NA>15220312135.1110497경기도 고양시 덕양구 화중로 ***, 비젼타워** **층 ****호 (화정동)경기도 고양시 덕양구 화정동 *** 비젼타워**412-827<NA><NA>식품운반업185054.432621459321.642285식품운반업00<NA><NA>000000N<NA><NA><NA>
시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수보증금액월세금액다중이용업소여부시설총규모전통업소지정번호전통업소음식
1670화성시케이에스에프수산물협동조합20140801<NA><NA>폐업 등20170907<NA><NA><NA>경기도 화성시 정남면 서봉로***번길 **-**, A동경기도 화성시 정남면 문학리 ***-*번지 A동44596137.153966126.952243<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
1671화성시농업회사법인(주)제이에프에스20070620<NA><NA>폐업 등20120509<NA><NA><NA>경기도 화성시 봉담읍 쇠틀길 **경기도 화성시 봉담읍 수기리 **-*번지44590437.200437126.976755<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
1672화성시애니푸드20070531<NA><NA>폐업 등20080703<NA><NA><NA><NA>경기도 화성시 오산동 ***-****번지 ((주)애니푸드 내)44515037.202138127.090495<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
1673화성시(주)애니푸드20070404<NA><NA>폐업 등20100122<NA><NA><NA><NA>경기도 화성시 오산동 ***-****번지44515037.202138127.090495<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
1674화성시(주)영림개발20060703<NA><NA>폐업 등20060703<NA><NA><NA>경기도 화성시 장안면 *.*만세로 ***경기도 화성시 장안면 수촌리 ***-*번지44594437.103719126.84173<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
1675화성시무지개식품20110818<NA><NA>폐업 등20151016<NA><NA><NA>경기도 화성시 병점중앙로***번길 **, ***호 (진안동)경기도 화성시 진안동 ***-*번지 ***호44539037.21393127.037207<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
1676화성시주식회사 자연지기20111222<NA><NA>폐업 등20130801<NA><NA><NA>경기도 화성시 매송면 화성로****번길 **-*, *층경기도 화성시 매송면 원평리 ***-**번지 *층44583237.252178126.924583<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
1677화성시준유통20101028<NA><NA>폐업 등20160325<NA><NA><NA>경기도 화성시 효행로 ***-* (안녕동,(A동 일부))경기도 화성시 안녕동 **-**번지 (A동 일부)44538037.202455127.012632<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
1678화성시길샘C&F20080711<NA><NA>폐업 등20151016<NA><NA><NA>경기도 화성시 용주로**번길 * (안녕동,외*필지)경기도 화성시 안녕동 **-**번지 외*필지44538037.206261127.013036<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
1679화성시씨푸드월드20040913<NA><NA>폐업 등20150914<NA><NA><NA>경기도 화성시 봉담읍 왕림*길 **경기도 화성시 봉담읍 왕림리 ***-*번지44590637.191997126.935982<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>

Duplicate rows

Most frequently occurring

시군명사업장명인허가일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값위생업태명남성종사자수여성종사자수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수보증금액월세금액다중이용업소여부# duplicates
0광주시리치운반20030618<NA>폐업 등20070724<NA><NA><NA>경기도 광주시 중앙로 ***경기도 광주시 경안동 ***-**번지46480637.414865127.257092<NA><NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA>N2
1성남시(주)이안지엘에스2014-06-202폐업2023-11-2002 575 014110.013494경기도 성남시 분당구 대왕판교로 *** (삼평동, 유스페이스* B-****호 일부)경기도 성남시 분당구 삼평동 *** 유스페이스* B-****호 일부463-400<NA><NA>식품운반업209374.87957433334.937936식품운반업00000000N2
2성남시주식회사 미서운수2017-01-062폐업2023-11-2002 575 01410.013494경기도 성남시 분당구 대왕판교로 *** (삼평동, 유스페이스* B-****호 일부)경기도 성남시 분당구 삼평동 *** 유스페이스* B-****호 일부463-400<NA><NA>식품운반업209374.87957433334.937936식품운반업00000000N2