Overview

Dataset statistics

Number of variables33
Number of observations417
Missing cells4555
Missing cells (%)33.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory116.2 KiB
Average record size in memory285.3 B

Variable types

Categorical12
Text5
DateTime2
Unsupported6
Numeric7
Boolean1

Alerts

위생업태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
공장생산직종업원수 is highly imbalanced (62.3%)Imbalance
보증금액 is highly imbalanced (54.1%)Imbalance
월세금액 is highly imbalanced (54.1%)Imbalance
인허가취소일자 has 417 (100.0%) missing valuesMissing
폐업일자 has 293 (70.3%) missing valuesMissing
소재지시설전화번호 has 299 (71.7%) missing valuesMissing
소재지면적정보 has 277 (66.4%) missing valuesMissing
도로명우편번호 has 278 (66.7%) missing valuesMissing
소재지도로명주소 has 30 (7.2%) missing valuesMissing
WGS84위도 has 12 (2.9%) missing valuesMissing
WGS84경도 has 12 (2.9%) missing valuesMissing
X좌표값 has 282 (67.6%) missing valuesMissing
Y좌표값 has 282 (67.6%) missing valuesMissing
영업장주변구분명 has 417 (100.0%) missing valuesMissing
등급구분명 has 417 (100.0%) missing valuesMissing
공장사무직종업원수 has 288 (69.1%) missing valuesMissing
시설총규모 has 417 (100.0%) missing valuesMissing
전통업소지정번호 has 417 (100.0%) missing valuesMissing
전통업소음식 has 417 (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
공장사무직종업원수 has 115 (27.6%) zerosZeros

Reproduction

Analysis started2023-12-10 22:33:08.036203
Analysis finished2023-12-10 22:33:08.638444
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct23
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
용인시
111 
이천시
75 
광주시
54 
평택시
32 
안성시
28 
Other values (18)
117 

Length

Max length4
Median length3
Mean length3.0143885
Min length3

Unique

Unique3 ?
Unique (%)0.7%

Sample

1st row고양시
2nd row고양시
3rd row고양시
4th row광주시
5th row광주시

Common Values

ValueCountFrequency (%)
용인시 111
26.6%
이천시 75
18.0%
광주시 54
12.9%
평택시 32
 
7.7%
안성시 28
 
6.7%
화성시 19
 
4.6%
오산시 18
 
4.3%
김포시 12
 
2.9%
여주시 8
 
1.9%
시흥시 8
 
1.9%
Other values (13) 52
12.5%

Length

2023-12-11T07:33:08.695044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용인시 111
26.6%
이천시 75
18.0%
광주시 54
12.9%
평택시 32
 
7.7%
안성시 28
 
6.7%
화성시 19
 
4.6%
오산시 18
 
4.3%
김포시 12
 
2.9%
여주시 8
 
1.9%
시흥시 8
 
1.9%
Other values (13) 52
12.5%

사업장명
Text

Distinct354
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2023-12-11T07:33:08.872816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length9.558753
Min length2

Characters and Unicode

Total characters3986
Distinct characters307
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

Unique310 ?
Unique (%)74.3%

Sample

1st row(주)빙그레
2nd row일산냉장
3rd row세림상사
4th row에이치엘홀딩스 곤지암냉장
5th row주식회사 팀프레시
ValueCountFrequency (%)
주식회사 61
 
11.0%
주)비지에프로지스 7
 
1.3%
주)동원홈푸드 6
 
1.1%
주)제때 5
 
0.9%
팀프레시 5
 
0.9%
씨제이대한통운 5
 
0.9%
화인유통(주 5
 
0.9%
주)아워홈 4
 
0.7%
주)에스피씨지에프에스 4
 
0.7%
스마트푸드네트웍스 4
 
0.7%
Other values (385) 448
80.9%
2023-12-11T07:33:09.207496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 353
 
8.9%
) 272
 
6.8%
( 269
 
6.7%
스 168
 
4.2%
137
 
3.4%
지 98
 
2.5%
사 91
 
2.3%
이 89
 
2.2%
에 81
 
2.0%
물 77
 
1.9%
Other values (297) 2351
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3249
81.5%
Close Punctuation 272
 
6.8%
Open Punctuation 269
 
6.7%
Space Separator 137
 
3.4%
Uppercase Letter 36
 
0.9%
Lowercase Letter 10
 
0.3%
Decimal Number 7
 
0.2%
Other Punctuation 5
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 353
 
10.9%
스 168
 
5.2%
지 98
 
3.0%
사 91
 
2.8%
이 89
 
2.7%
에 81
 
2.5%
물 77
 
2.4%
류 77
 
2.4%
식 77
 
2.4%
회 76
 
2.3%
Other values (268) 2062
63.5%
Uppercase Letter
ValueCountFrequency (%)
C 7
19.4%
J 5
13.9%
S 5
13.9%
A 5
13.9%
F 4
11.1%
H 3
8.3%
T 2
 
5.6%
B 2
 
5.6%
K 1
 
2.8%
D 1
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
o 3
30.0%
e 2
20.0%
r 1
 
10.0%
c 1
 
10.0%
d 1
 
10.0%
f 1
 
10.0%
y 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
40.0%
, 1
20.0%
& 1
20.0%
. 1
20.0%
Decimal Number
ValueCountFrequency (%)
2 4
57.1%
1 2
28.6%
3 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 272
100.0%
Open Punctuation
ValueCountFrequency (%)
( 269
100.0%
Space Separator
ValueCountFrequency (%)
137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3249
81.5%
Common 691
 
17.3%
Latin 46
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 353
 
10.9%
스 168
 
5.2%
지 98
 
3.0%
사 91
 
2.8%
이 89
 
2.7%
에 81
 
2.5%
물 77
 
2.4%
류 77
 
2.4%
식 77
 
2.4%
회 76
 
2.3%
Other values (268) 2062
63.5%
Latin
ValueCountFrequency (%)
C 7
15.2%
J 5
10.9%
S 5
10.9%
A 5
10.9%
F 4
8.7%
H 3
 
6.5%
o 3
 
6.5%
e 2
 
4.3%
T 2
 
4.3%
B 2
 
4.3%
Other values (8) 8
17.4%
Common
ValueCountFrequency (%)
) 272
39.4%
( 269
38.9%
137
19.8%
2 4
 
0.6%
1 2
 
0.3%
/ 2
 
0.3%
, 1
 
0.1%
- 1
 
0.1%
3 1
 
0.1%
& 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3249
81.5%
ASCII 737
 
18.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 353
 
10.9%
스 168
 
5.2%
지 98
 
3.0%
사 91
 
2.8%
이 89
 
2.7%
에 81
 
2.5%
물 77
 
2.4%
류 77
 
2.4%
식 77
 
2.4%
회 76
 
2.3%
Other values (268) 2062
63.5%
ASCII
ValueCountFrequency (%)
) 272
36.9%
( 269
36.5%
137
18.6%
C 7
 
0.9%
J 5
 
0.7%
S 5
 
0.7%
A 5
 
0.7%
F 4
 
0.5%
2 4
 
0.5%
H 3
 
0.4%
Other values (19) 26
 
3.5%

인허가일자
Date

Distinct350
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum1976-07-12 00:00:00
Maximum2023-11-23 00:00:00
2023-12-11T07:33:09.323701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:09.436378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing417
Missing (%)100.0%
Memory size3.8 KiB

영업상태구분코드
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
276 
1
124 
2
 
17

Length

Max length4
Median length4
Mean length2.9856115
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 276
66.2%
1 124
29.7%
2 17
 
4.1%

Length

2023-12-11T07:33:09.555754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:09.672907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 276
66.2%
1 124
29.7%
2 17
 
4.1%

영업상태명
Categorical

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
운영중
169 
영업
124 
폐업 등
107 
폐업
17 

Length

Max length4
Median length3
Mean length2.9184652
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 169
40.5%
영업 124
29.7%
폐업 등 107
25.7%
폐업 17
 
4.1%

Length

2023-12-11T07:33:09.776284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:09.887889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 169
32.3%
영업 124
23.7%
폐업 124
23.7%
등 107
20.4%

폐업일자
Date

MISSING 

Distinct116
Distinct (%)93.5%
Missing293
Missing (%)70.3%
Memory size3.4 KiB
Minimum2000-12-19 00:00:00
Maximum2023-12-05 00:00:00
2023-12-11T07:33:09.990302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:10.108691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지시설전화번호
Text

MISSING 

Distinct108
Distinct (%)91.5%
Missing299
Missing (%)71.7%
Memory size3.4 KiB
2023-12-11T07:33:10.378222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.432203
Min length8

Characters and Unicode

Total characters1349
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

Unique101 ?
Unique (%)85.6%

Sample

1st row031 80274717
2nd row02 423 0525
3rd row031 7629934
4th row031 334 6166
5th row03180279270
ValueCountFrequency (%)
031 74
27.3%
02 18
 
6.6%
0525 5
 
1.8%
423 5
 
1.8%
070 4
 
1.5%
645 4
 
1.5%
637 3
 
1.1%
631 3
 
1.1%
6344058 2
 
0.7%
260 2
 
0.7%
Other values (141) 151
55.7%
2023-12-11T07:33:10.767207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 220
16.3%
3 171
12.7%
1 171
12.7%
169
12.5%
2 129
9.6%
6 113
8.4%
7 82
 
6.1%
9 76
 
5.6%
4 73
 
5.4%
5 73
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1180
87.5%
Space Separator 169
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 220
18.6%
3 171
14.5%
1 171
14.5%
2 129
10.9%
6 113
9.6%
7 82
 
6.9%
9 76
 
6.4%
4 73
 
6.2%
5 73
 
6.2%
8 72
 
6.1%
Space Separator
ValueCountFrequency (%)
169
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1349
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 220
16.3%
3 171
12.7%
1 171
12.7%
169
12.5%
2 129
9.6%
6 113
8.4%
7 82
 
6.1%
9 76
 
5.6%
4 73
 
5.4%
5 73
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1349
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 220
16.3%
3 171
12.7%
1 171
12.7%
169
12.5%
2 129
9.6%
6 113
8.4%
7 82
 
6.1%
9 76
 
5.6%
4 73
 
5.4%
5 73
 
5.4%

소재지면적정보
Real number (ℝ)

MISSING 

Distinct139
Distinct (%)99.3%
Missing277
Missing (%)66.4%
Infinite0
Infinite (%)0.0%
Mean7485.9524
Minimum35
Maximum101160.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-11T07:33:10.901244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile262.98
Q11487.7825
median3296.17
Q39297.825
95-th percentile25143.703
Maximum101160.26
Range101125.26
Interquartile range (IQR)7810.0425

Descriptive statistics

Standard deviation11383.703
Coefficient of variation (CV)1.5206753
Kurtosis32.935108
Mean7485.9524
Median Absolute Deviation (MAD)2354.85
Skewness4.6704197
Sum1048033.3
Variance1.295887 × 108
MonotonicityNot monotonic
2023-12-11T07:33:11.021897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5566.0 2
 
0.5%
5680.0 1
 
0.2%
660.0 1
 
0.2%
9629.4 1
 
0.2%
3046.13 1
 
0.2%
2353.71 1
 
0.2%
1086.89 1
 
0.2%
1821.4 1
 
0.2%
297.0 1
 
0.2%
7421.66 1
 
0.2%
Other values (129) 129
30.9%
(Missing) 277
66.4%
ValueCountFrequency (%)
35.0 1
0.2%
36.0 1
0.2%
48.4 1
0.2%
57.6 1
0.2%
120.0 1
0.2%
172.92 1
0.2%
198.0 1
0.2%
266.4 1
0.2%
297.0 1
0.2%
528.0 1
0.2%
ValueCountFrequency (%)
101160.26 1
0.2%
38958.37 1
0.2%
37623.21 1
0.2%
34364.57 1
0.2%
31548.56 1
0.2%
26821.48 1
0.2%
25506.29 1
0.2%
25124.62 1
0.2%
24360.78 1
0.2%
24159.41 1
0.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)54.0%
Missing278
Missing (%)66.7%
Infinite0
Infinite (%)0.0%
Mean16432.05
Minimum10135
Maximum18524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-11T07:33:11.130281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10135
5-th percentile11910.5
Q117028.5
median17382
Q317513
95-th percentile18138.3
Maximum18524
Range8389
Interquartile range (IQR)484.5

Descriptive statistics

Standard deviation2188.3969
Coefficient of variation (CV)0.13317857
Kurtosis1.0900129
Mean16432.05
Median Absolute Deviation (MAD)283
Skewness-1.5814912
Sum2284055
Variance4789081.1
MonotonicityNot monotonic
2023-12-11T07:33:11.241076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17118 7
 
1.7%
18137 7
 
1.7%
17501 6
 
1.4%
17392 6
 
1.4%
17396 5
 
1.2%
18126 5
 
1.2%
17525 5
 
1.2%
12814 5
 
1.2%
17402 4
 
1.0%
17115 4
 
1.0%
Other values (65) 85
 
20.4%
(Missing) 278
66.7%
ValueCountFrequency (%)
10135 3
0.7%
10136 1
 
0.2%
11160 1
 
0.2%
11414 1
 
0.2%
11510 1
 
0.2%
11955 1
 
0.2%
12047 1
 
0.2%
12659 1
 
0.2%
12729 2
0.5%
12730 1
 
0.2%
ValueCountFrequency (%)
18524 1
 
0.2%
18522 1
 
0.2%
18512 1
 
0.2%
18487 1
 
0.2%
18465 2
 
0.5%
18150 1
 
0.2%
18137 7
1.7%
18126 5
1.2%
17967 1
 
0.2%
17789 1
 
0.2%

소재지도로명주소
Text

MISSING 

Distinct335
Distinct (%)86.6%
Missing30
Missing (%)7.2%
Memory size3.4 KiB
2023-12-11T07:33:11.519413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length45
Mean length28.330749
Min length14

Characters and Unicode

Total characters10964
Distinct characters245
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

Unique287 ?
Unique (%)74.2%

Sample

1st row경기도 고양시 덕양구 강매로 259, 1층 (강매동)
2nd row경기도 고양시 일산동구 장항로225번길 195 (장항동,외1필지 A동(1층일부,2층전체),B동(1,2층전체))
3rd row경기도 고양시 덕양구 행신로329번길 9
4th row경기도 광주시 도척면 도척로 401-98, 유유물류센터 1동
5th row경기도 광주시 옥토골길 7, 4,6동 (태전동)
ValueCountFrequency (%)
경기도 387
 
15.9%
용인시 109
 
4.5%
이천시 72
 
3.0%
처인구 63
 
2.6%
광주시 54
 
2.2%
1층 45
 
1.9%
기흥구 44
 
1.8%
평택시 29
 
1.2%
마장면 26
 
1.1%
안성시 25
 
1.0%
Other values (699) 1578
64.9%
2023-12-11T07:33:12.029537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2049
 
18.7%
기 453
 
4.1%
1 433
 
3.9%
도 421
 
3.8%
경 410
 
3.7%
시 397
 
3.6%
로 363
 
3.3%
2 296
 
2.7%
, 285
 
2.6%
동 245
 
2.2%
Other values (235) 5612
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6252
57.0%
Space Separator 2049
 
18.7%
Decimal Number 1864
 
17.0%
Other Punctuation 290
 
2.6%
Close Punctuation 171
 
1.6%
Open Punctuation 171
 
1.6%
Dash Punctuation 105
 
1.0%
Uppercase Letter 47
 
0.4%
Math Symbol 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 453
 
7.2%
도 421
 
6.7%
경 410
 
6.6%
시 397
 
6.3%
로 363
 
5.8%
동 245
 
3.9%
층 223
 
3.6%
인 178
 
2.8%
면 166
 
2.7%
구 139
 
2.2%
Other values (211) 3257
52.1%
Decimal Number
ValueCountFrequency (%)
1 433
23.2%
2 296
15.9%
3 223
12.0%
4 168
 
9.0%
5 140
 
7.5%
7 133
 
7.1%
6 130
 
7.0%
0 129
 
6.9%
8 109
 
5.8%
9 103
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
A 22
46.8%
B 18
38.3%
C 4
 
8.5%
P 1
 
2.1%
F 1
 
2.1%
D 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 285
98.3%
. 4
 
1.4%
/ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
2049
100.0%
Close Punctuation
ValueCountFrequency (%)
) 171
100.0%
Open Punctuation
ValueCountFrequency (%)
( 171
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 105
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6252
57.0%
Common 4665
42.5%
Latin 47
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 453
 
7.2%
도 421
 
6.7%
경 410
 
6.6%
시 397
 
6.3%
로 363
 
5.8%
동 245
 
3.9%
층 223
 
3.6%
인 178
 
2.8%
면 166
 
2.7%
구 139
 
2.2%
Other values (211) 3257
52.1%
Common
ValueCountFrequency (%)
2049
43.9%
1 433
 
9.3%
2 296
 
6.3%
, 285
 
6.1%
3 223
 
4.8%
) 171
 
3.7%
( 171
 
3.7%
4 168
 
3.6%
5 140
 
3.0%
7 133
 
2.9%
Other values (8) 596
 
12.8%
Latin
ValueCountFrequency (%)
A 22
46.8%
B 18
38.3%
C 4
 
8.5%
P 1
 
2.1%
F 1
 
2.1%
D 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6252
57.0%
ASCII 4712
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2049
43.5%
1 433
 
9.2%
2 296
 
6.3%
, 285
 
6.0%
3 223
 
4.7%
) 171
 
3.6%
( 171
 
3.6%
4 168
 
3.6%
5 140
 
3.0%
7 133
 
2.8%
Other values (14) 643
 
13.6%
Hangul
ValueCountFrequency (%)
기 453
 
7.2%
도 421
 
6.7%
경 410
 
6.6%
시 397
 
6.3%
로 363
 
5.8%
동 245
 
3.9%
층 223
 
3.6%
인 178
 
2.8%
면 166
 
2.7%
구 139
 
2.2%
Other values (211) 3257
52.1%

소재지지번주소
Text

Distinct384
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2023-12-11T07:33:12.353068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length95
Median length49
Mean length26.071942
Min length16

Characters and Unicode

Total characters10872
Distinct characters237
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

Unique359 ?
Unique (%)86.1%

Sample

1st row경기도 고양시 덕양구 강매동 90-1번지 1층
2nd row경기도 고양시 일산동구 장항동 548-12번지 외1필지 A동(1층일부,2층전체),B동(1,2층전체)
3rd row경기도 고양시 덕양구 행신동 243-1번지
4th row경기도 광주시 도척면 진우리 1007 유유물류센터
5th row경기도 광주시 태전동 503-1 4,6동
ValueCountFrequency (%)
경기도 417
 
17.3%
용인시 111
 
4.6%
이천시 75
 
3.1%
처인구 63
 
2.6%
광주시 54
 
2.2%
기흥구 46
 
1.9%
평택시 32
 
1.3%
마장면 28
 
1.2%
안성시 28
 
1.2%
1층 26
 
1.1%
Other values (751) 1531
63.5%
2023-12-11T07:33:12.830043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2127
 
19.6%
기 465
 
4.3%
도 436
 
4.0%
시 428
 
3.9%
1 418
 
3.8%
경 417
 
3.8%
지 417
 
3.8%
- 296
 
2.7%
번 277
 
2.5%
2 258
 
2.4%
Other values (227) 5333
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6317
58.1%
Space Separator 2127
 
19.6%
Decimal Number 1917
 
17.6%
Dash Punctuation 296
 
2.7%
Other Punctuation 89
 
0.8%
Uppercase Letter 40
 
0.4%
Open Punctuation 39
 
0.4%
Close Punctuation 38
 
0.3%
Math Symbol 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 465
 
7.4%
도 436
 
6.9%
시 428
 
6.8%
경 417
 
6.6%
지 417
 
6.6%
번 277
 
4.4%
동 258
 
4.1%
리 249
 
3.9%
면 178
 
2.8%
인 174
 
2.8%
Other values (203) 3018
47.8%
Decimal Number
ValueCountFrequency (%)
1 418
21.8%
2 258
13.5%
5 232
12.1%
3 208
10.9%
4 182
9.5%
6 164
 
8.6%
7 145
 
7.6%
9 112
 
5.8%
0 106
 
5.5%
8 92
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
A 19
47.5%
B 12
30.0%
C 4
 
10.0%
F 2
 
5.0%
D 2
 
5.0%
P 1
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 84
94.4%
. 4
 
4.5%
/ 1
 
1.1%
Space Separator
ValueCountFrequency (%)
2127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 296
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6317
58.1%
Common 4515
41.5%
Latin 40
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 465
 
7.4%
도 436
 
6.9%
시 428
 
6.8%
경 417
 
6.6%
지 417
 
6.6%
번 277
 
4.4%
동 258
 
4.1%
리 249
 
3.9%
면 178
 
2.8%
인 174
 
2.8%
Other values (203) 3018
47.8%
Common
ValueCountFrequency (%)
2127
47.1%
1 418
 
9.3%
- 296
 
6.6%
2 258
 
5.7%
5 232
 
5.1%
3 208
 
4.6%
4 182
 
4.0%
6 164
 
3.6%
7 145
 
3.2%
9 112
 
2.5%
Other values (8) 373
 
8.3%
Latin
ValueCountFrequency (%)
A 19
47.5%
B 12
30.0%
C 4
 
10.0%
F 2
 
5.0%
D 2
 
5.0%
P 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6317
58.1%
ASCII 4555
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2127
46.7%
1 418
 
9.2%
- 296
 
6.5%
2 258
 
5.7%
5 232
 
5.1%
3 208
 
4.6%
4 182
 
4.0%
6 164
 
3.6%
7 145
 
3.2%
9 112
 
2.5%
Other values (14) 413
 
9.1%
Hangul
ValueCountFrequency (%)
기 465
 
7.4%
도 436
 
6.9%
시 428
 
6.8%
경 417
 
6.6%
지 417
 
6.6%
번 277
 
4.4%
동 258
 
4.1%
리 249
 
3.9%
면 178
 
2.8%
인 174
 
2.8%
Other values (203) 3018
47.8%

소재지우편번호
Text

Distinct223
Distinct (%)53.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2023-12-11T07:33:13.140615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2326139
Min length5

Characters and Unicode

Total characters2599
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

Unique143 ?
Unique (%)34.3%

Sample

1st row412290
2nd row410835
3rd row412823
4th row464-883
5th row464-805
ValueCountFrequency (%)
467811 9
 
2.2%
467822 8
 
1.9%
447-802 7
 
1.7%
446930 7
 
1.7%
17118 7
 
1.7%
446901 7
 
1.7%
456-932 6
 
1.4%
467-822 6
 
1.4%
467-811 6
 
1.4%
449824 6
 
1.4%
Other values (213) 348
83.5%
2023-12-11T07:33:13.625782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 660
25.4%
8 320
12.3%
1 273
10.5%
6 270
10.4%
5 187
 
7.2%
9 168
 
6.5%
2 160
 
6.2%
0 158
 
6.1%
7 156
 
6.0%
3 125
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2477
95.3%
Dash Punctuation 122
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 660
26.6%
8 320
12.9%
1 273
11.0%
6 270
10.9%
5 187
 
7.5%
9 168
 
6.8%
2 160
 
6.5%
0 158
 
6.4%
7 156
 
6.3%
3 125
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 660
25.4%
8 320
12.3%
1 273
10.5%
6 270
10.4%
5 187
 
7.2%
9 168
 
6.5%
2 160
 
6.2%
0 158
 
6.1%
7 156
 
6.0%
3 125
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 660
25.4%
8 320
12.3%
1 273
10.5%
6 270
10.4%
5 187
 
7.2%
9 168
 
6.5%
2 160
 
6.2%
0 158
 
6.1%
7 156
 
6.0%
3 125
 
4.8%

WGS84위도
Real number (ℝ)

MISSING 

Distinct276
Distinct (%)68.1%
Missing12
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean37.26989
Minimum36.936686
Maximum37.863977
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-11T07:33:13.860823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.936686
5-th percentile37.035922
Q137.175396
median37.25034
Q337.330883
95-th percentile37.621304
Maximum37.863977
Range0.92729159
Interquartile range (IQR)0.15548638

Descriptive statistics

Standard deviation0.16486194
Coefficient of variation (CV)0.0044234618
Kurtosis2.2487358
Mean37.26989
Median Absolute Deviation (MAD)0.080067508
Skewness1.1563194
Sum15094.306
Variance0.027179458
MonotonicityNot monotonic
2023-12-11T07:33:14.169211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.1402636525 9
 
2.2%
37.2801867842 6
 
1.4%
37.1435197322 5
 
1.2%
37.2481972971 5
 
1.2%
37.2441563133 5
 
1.2%
37.0880948518 5
 
1.2%
37.0359217163 4
 
1.0%
37.1441159983 4
 
1.0%
37.1766221327 4
 
1.0%
37.1290957631 3
 
0.7%
Other values (266) 355
85.1%
(Missing) 12
 
2.9%
ValueCountFrequency (%)
36.9366856996 1
 
0.2%
36.9391397178 1
 
0.2%
36.9600517251 1
 
0.2%
36.9636058181 1
 
0.2%
36.9637302172 1
 
0.2%
36.9666145903 1
 
0.2%
36.9686047446 1
 
0.2%
36.9732433578 3
0.7%
36.9773884238 1
 
0.2%
36.989298406 1
 
0.2%
ValueCountFrequency (%)
37.8639772857 1
0.2%
37.8623909271 1
0.2%
37.8318331549 2
0.5%
37.8278696689 1
0.2%
37.8153064875 1
0.2%
37.7874154989 2
0.5%
37.7692567685 1
0.2%
37.742760402 1
0.2%
37.7195934825 1
0.2%
37.7192147347 1
0.2%

WGS84경도
Real number (ℝ)

MISSING 

Distinct276
Distinct (%)68.1%
Missing12
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean127.19175
Minimum126.58776
Maximum127.65174
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-11T07:33:14.636168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.58776
5-th percentile126.79353
Q1127.08948
median127.20045
Q3127.3537
95-th percentile127.48177
Maximum127.65174
Range1.0639873
Interquartile range (IQR)0.26422037

Descriptive statistics

Standard deviation0.20085295
Coefficient of variation (CV)0.001579135
Kurtosis-0.098828406
Mean127.19175
Median Absolute Deviation (MAD)0.13925495
Skewness-0.42702519
Sum51512.658
Variance0.040341907
MonotonicityNot monotonic
2023-12-11T07:33:14.777455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0674375076 9
 
2.2%
127.3979678918 6
 
1.4%
127.0581969558 5
 
1.2%
127.4235956691 5
 
1.2%
127.3611355535 5
 
1.2%
127.2078316823 5
 
1.2%
127.0948811946 4
 
1.0%
127.1596928621 4
 
1.0%
127.1794974943 4
 
1.0%
127.4272505884 3
 
0.7%
Other values (266) 355
85.1%
(Missing) 12
 
2.9%
ValueCountFrequency (%)
126.5877568553 1
 
0.2%
126.6361545321 1
 
0.2%
126.6369688009 1
 
0.2%
126.6984781713 1
 
0.2%
126.7023455373 3
0.7%
126.714982277 2
0.5%
126.7161805896 1
 
0.2%
126.7627184312 1
 
0.2%
126.7640695722 1
 
0.2%
126.7818864108 1
 
0.2%
ValueCountFrequency (%)
127.6517441137 1
 
0.2%
127.6412538656 1
 
0.2%
127.6241058427 1
 
0.2%
127.5922014883 1
 
0.2%
127.5679513853 3
0.7%
127.5492784926 2
0.5%
127.5275862817 1
 
0.2%
127.5177828305 1
 
0.2%
127.511238777 1
 
0.2%
127.4991312751 1
 
0.2%

업태구분명정보
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
276 
식품냉동.냉장업
141 

Length

Max length8
Median length4
Mean length5.352518
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 276
66.2%
식품냉동.냉장업 141
33.8%

Length

2023-12-11T07:33:14.909575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:15.019250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 276
66.2%
식품냉동.냉장업 141
33.8%

X좌표값
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)74.1%
Missing282
Missing (%)67.6%
Infinite0
Infinite (%)0.0%
Mean220018.92
Minimum173599.09
Maximum256824.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-11T07:33:15.148619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173599.09
5-th percentile193610.23
Q1207914.05
median218386.26
Q3233754.79
95-th percentile243877.27
Maximum256824.61
Range83225.52
Interquartile range (IQR)25840.749

Descriptive statistics

Standard deviation16671.206
Coefficient of variation (CV)0.075771696
Kurtosis-0.32322941
Mean220018.92
Median Absolute Deviation (MAD)12745.195
Skewness-0.3208691
Sum29702554
Variance2.7792912 × 108
MonotonicityNot monotonic
2023-12-11T07:33:15.328488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205912.898384165 7
 
1.7%
218386.261739731 5
 
1.2%
214119.897168312 4
 
1.0%
215898.384277154 4
 
1.0%
231944.627841382 3
 
0.7%
205265.557837448 3
 
0.7%
237883.259381491 3
 
0.7%
202408.08118425 3
 
0.7%
231131.456830912 2
 
0.5%
236260.869251761 2
 
0.5%
Other values (90) 99
 
23.7%
(Missing) 282
67.6%
ValueCountFrequency (%)
173599.091691681 1
0.2%
180792.851887727 1
0.2%
180879.061233099 1
0.2%
180918.027998803 1
0.2%
181515.408945204 1
0.2%
188754.410715334 1
0.2%
188800.430053243 1
0.2%
195671.578803296 1
0.2%
195977.247104537 1
0.2%
197846.675917106 1
0.2%
ValueCountFrequency (%)
256824.611593715 1
0.2%
248822.639728979 1
0.2%
246711.757597769 1
0.2%
245934.254046475 1
0.2%
245405.354618581 1
0.2%
244194.323056592 1
0.2%
244083.227304661 1
0.2%
243789.000912988 1
0.2%
243724.148238442 2
0.5%
243559.523553866 1
0.2%

Y좌표값
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)74.1%
Missing282
Missing (%)67.6%
Infinite0
Infinite (%)0.0%
Mean415832.04
Minimum381828.97
Maximum484512.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-11T07:33:15.491470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum381828.97
5-th percentile398511.14
Q1404559.48
median414430.85
Q3421686.45
95-th percentile454485.65
Maximum484512.56
Range102683.59
Interquartile range (IQR)17126.971

Descriptive statistics

Standard deviation16805.441
Coefficient of variation (CV)0.040414011
Kurtosis4.4211582
Mean415832.04
Median Absolute Deviation (MAD)9249.8367
Skewness1.751053
Sum56137325
Variance2.8242284 × 108
MonotonicityNot monotonic
2023-12-11T07:33:15.674451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
404249.209315327 7
 
1.7%
398511.138734236 5
 
1.2%
404726.158193274 4
 
1.0%
408316.533576664 4
 
1.0%
415881.805362322 3
 
0.7%
404623.916863931 3
 
0.7%
403116.03339656 3
 
0.7%
401495.158206034 3
 
0.7%
418883.852505601 2
 
0.5%
415371.641888509 2
 
0.5%
Other values (90) 99
 
23.7%
(Missing) 282
67.6%
ValueCountFrequency (%)
381828.9673366 1
 
0.2%
384658.086055309 1
 
0.2%
392693.934217221 1
 
0.2%
396500.340590474 1
 
0.2%
398453.973690799 1
 
0.2%
398511.138734236 5
1.2%
398558.631480265 1
 
0.2%
399655.277915152 1
 
0.2%
401268.188175509 1
 
0.2%
401315.238097155 1
 
0.2%
ValueCountFrequency (%)
484512.556615829 1
0.2%
481028.622066699 1
0.2%
476142.562242661 1
0.2%
466418.397108474 1
0.2%
455362.939668502 1
0.2%
455268.884337207 1
0.2%
455205.328587106 1
0.2%
454177.216142397 1
0.2%
453276.579208128 1
0.2%
435069.545543643 1
0.2%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
식품냉동.냉장업
417 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row식품냉동.냉장업
2nd row식품냉동.냉장업
3rd row식품냉동.냉장업
4th row식품냉동.냉장업
5th row식품냉동.냉장업

Common Values

ValueCountFrequency (%)
식품냉동.냉장업 417
100.0%

Length

2023-12-11T07:33:15.811960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:15.920950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품냉동.냉장업 417
100.0%

남성종사자수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
298 
0
119 

Length

Max length4
Median length4
Mean length3.1438849
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 298
71.5%
0 119
 
28.5%

Length

2023-12-11T07:33:16.059196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:16.163484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 298
71.5%
0 119
 
28.5%

여성종사자수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
298 
0
119 

Length

Max length4
Median length4
Mean length3.1438849
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 298
71.5%
0 119
 
28.5%

Length

2023-12-11T07:33:16.276208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:16.424352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 298
71.5%
0 119
 
28.5%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing417
Missing (%)100.0%
Memory size3.8 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing417
Missing (%)100.0%
Memory size3.8 KiB

본사종업원수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
288 
0
129 

Length

Max length4
Median length4
Mean length3.0719424
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 288
69.1%
0 129
30.9%

Length

2023-12-11T07:33:16.524762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:16.640627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 288
69.1%
0 129
30.9%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)10.9%
Missing288
Missing (%)69.1%
Infinite0
Infinite (%)0.0%
Mean4.4186047
Minimum0
Maximum300
Zeros115
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-11T07:33:16.735174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8.6
Maximum300
Range300
Interquartile range (IQR)0

Descriptive statistics

Standard deviation29.785351
Coefficient of variation (CV)6.7408953
Kurtosis81.828338
Mean4.4186047
Median Absolute Deviation (MAD)0
Skewness8.8029863
Sum570
Variance887.16715
MonotonicityNot monotonic
2023-12-11T07:33:16.854603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 115
 
27.6%
6 2
 
0.5%
8 1
 
0.2%
9 1
 
0.2%
300 1
 
0.2%
24 1
 
0.2%
1 1
 
0.2%
5 1
 
0.2%
3 1
 
0.2%
22 1
 
0.2%
Other values (4) 4
 
1.0%
(Missing) 288
69.1%
ValueCountFrequency (%)
0 115
27.6%
1 1
 
0.2%
2 1
 
0.2%
3 1
 
0.2%
5 1
 
0.2%
6 2
 
0.5%
8 1
 
0.2%
9 1
 
0.2%
10 1
 
0.2%
18 1
 
0.2%
ValueCountFrequency (%)
300 1
0.2%
156 1
0.2%
24 1
0.2%
22 1
0.2%
18 1
0.2%
10 1
0.2%
9 1
0.2%
8 1
0.2%
6 2
0.5%
5 1
0.2%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
288 
0
128 
17
 
1

Length

Max length4
Median length4
Mean length3.0743405
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 288
69.1%
0 128
30.7%
17 1
 
0.2%

Length

2023-12-11T07:33:16.972989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:17.097121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 288
69.1%
0 128
30.7%
17 1
 
0.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
288 
0
125 
5
 
1
90
 
1
30
 
1

Length

Max length4
Median length4
Mean length3.0791367
Min length1

Unique

Unique4 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 288
69.1%
0 125
30.0%
5 1
 
0.2%
90 1
 
0.2%
30 1
 
0.2%
10 1
 
0.2%

Length

2023-12-11T07:33:17.219724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:17.339669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 288
69.1%
0 125
30.0%
5 1
 
0.2%
90 1
 
0.2%
30 1
 
0.2%
10 1
 
0.2%

보증금액
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
298 
0
116 
275440000
 
2
300000000
 
1

Length

Max length9
Median length4
Mean length3.2014388
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 298
71.5%
0 116
 
27.8%
275440000 2
 
0.5%
300000000 1
 
0.2%

Length

2023-12-11T07:33:17.470631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:17.573711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 298
71.5%
0 116
 
27.8%
275440000 2
 
0.5%
300000000 1
 
0.2%

월세금액
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
<NA>
298 
0
116 
96558000
 
2
45000000
 
1

Length

Max length8
Median length4
Mean length3.1942446
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 298
71.5%
0 116
 
27.8%
96558000 2
 
0.5%
45000000 1
 
0.2%

Length

2023-12-11T07:33:17.688290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:17.820928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 298
71.5%
0 116
 
27.8%
96558000 2
 
0.5%
45000000 1
 
0.2%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size549.0 B
False
417 
ValueCountFrequency (%)
False 417
100.0%
2023-12-11T07:33:17.914436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing417
Missing (%)100.0%
Memory size3.8 KiB

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing417
Missing (%)100.0%
Memory size3.8 KiB

전통업소음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing417
Missing (%)100.0%
Memory size3.8 KiB

Sample

시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수보증금액월세금액다중이용업소여부시설총규모전통업소지정번호전통업소음식
0고양시(주)빙그레20090929<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 덕양구 강매로 259, 1층 (강매동)경기도 고양시 덕양구 강매동 90-1번지 1층41229037.609635126.845454<NA><NA><NA>식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
1고양시일산냉장20080811<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산동구 장항로225번길 195 (장항동,외1필지 A동(1층일부,2층전체),B동(1,2층전체))경기도 고양시 일산동구 장항동 548-12번지 외1필지 A동(1층일부,2층전체),B동(1,2층전체)41083537.642027126.76407<NA><NA><NA>식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
2고양시세림상사20010413<NA><NA>폐업 등20121127<NA><NA><NA>경기도 고양시 덕양구 행신로329번길 9경기도 고양시 덕양구 행신동 243-1번지41282337.624221126.845961<NA><NA><NA>식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
3광주시에이치엘홀딩스 곤지암냉장2012-11-23<NA>1영업<NA>031 8027471731548.5612814경기도 광주시 도척면 도척로 401-98, 유유물류센터 1동경기도 광주시 도척면 진우리 1007 유유물류센터464-88337.312569127.343709식품냉동.냉장업230419.426001423414.907151식품냉동.냉장업<NA><NA><NA><NA>0000<NA><NA>N<NA><NA><NA>
4광주시주식회사 팀프레시2022-05-18<NA>1영업<NA>02 423 05251241.412783경기도 광주시 옥토골길 7, 4,6동 (태전동)경기도 광주시 태전동 503-1 4,6동464-80537.394202127.218928식품냉동.냉장업219318.976419432485.505477식품냉동.냉장업00<NA><NA>000000N<NA><NA><NA>
5광주시주식회사 멕시카나2020-03-24<NA>1영업<NA>031 7629934637.9412729경기도 광주시 초월읍 산수로508번길 11경기도 광주시 초월읍 신월리 480-2464-86437.405913127.310657식품냉동.냉장업227374.110268433814.943335식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
6광주시(주)피아이오2023-02-15<NA>1영업<NA>031 334 616616867.2912814경기도 광주시 도척면 도척로 401-85, 지1~3층경기도 광주시 도척면 진우리 1005-1 지하 1~3층 일부464-88337.314694127.342272식품냉동.냉장업230283.795786423680.685922식품냉동.냉장업00<NA><NA>000000N<NA><NA><NA>
7광주시비지에프로지스 프레시센터2022-08-18<NA>1영업<NA>031802792706451.6112801경기도 광주시 곤지암읍 신대길 134-14, B2층경기도 광주시 곤지암읍 신대리 280 B2층464-87337.364089127.334873식품냉동.냉장업229593.102321429159.909465식품냉동.냉장업00<NA><NA>000000N<NA><NA><NA>
8광주시대청냉장(주)2023-08-21<NA>1영업<NA>031 80173338857.9212729경기도 광주시 초월읍 산수로 370, 2, 지1, 지2층경기도 광주시 초월읍 신월리 666-3 2층(사무실), 지1,2층(창고)464-86437.394029127.313997식품냉동.냉장업227722.988992432461.548382식품냉동.냉장업00<NA><NA>000000N<NA><NA><NA>
9광주시(주)한익스프레스 광주오포센터2019-05-31<NA>1영업<NA>031 639 55951983.4812774경기도 광주시 오포로 614, 1층경기도 광주시 문형동 295-61277437.351629127.21483식품냉동.냉장업218966.716399427765.596148식품냉동.냉장업00<NA><NA>000000N<NA><NA><NA>
시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수보증금액월세금액다중이용업소여부시설총규모전통업소지정번호전통업소음식
407화성시토리2019-05-15<NA>2폐업2023-05-15<NA>35.018487경기도 화성시 동탄기흥로257번나길 30-3, 1층 일부호 (방교동)경기도 화성시 방교동 759-5 1층 일부호1848737.180617127.08948식품냉동.냉장업207875.410635408756.8725식품냉동.냉장업00<NA><NA>000000N<NA><NA><NA>
408화성시엘림20160623<NA><NA>폐업 등20160825<NA><NA><NA>경기도 화성시 향남읍 동오2길 45, A동 (2층하부)경기도 화성시 향남읍 동오리 118-6번지 2층 하부 A동44592937.135002126.962389<NA><NA><NA>식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
409화성시(주)씨케이원20031120<NA><NA>폐업 등20070601<NA><NA><NA><NA>경기도 화성시 영천동 559번지44513037.206383127.100773<NA><NA><NA>식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
410화성시(주)현대백화점H&S20030715<NA><NA>폐업 등20180518<NA><NA><NA><NA>경기도 화성시 영천동 582-1번지44513037.205721127.106416<NA><NA><NA>식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
411화성시(주)애니푸드20070404<NA><NA>폐업 등20100122<NA><NA><NA><NA>경기도 화성시 오산동 967-1238번지44515037.202138127.090495<NA><NA><NA>식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
412화성시벧델농축산20040830<NA><NA>폐업 등20051130<NA><NA><NA><NA>경기도 화성시 기산동 38-1번지44530037.217216127.054696<NA><NA><NA>식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
413화성시아주코퍼레이션(주) 기흥냉장20060310<NA><NA>폐업 등20120629<NA><NA><NA>경기도 화성시 동탄기흥로502번가길 29-4경기도 화성시 오산동 967-117번지44515037.20244127.096826<NA><NA><NA>식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
414화성시(주)현대그린푸드20050309<NA><NA>폐업 등20101224<NA><NA><NA><NA>경기도 화성시 영천동 582-1번지44513037.205721127.106416<NA><NA><NA>식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
415화성시기흥냉동20030807<NA><NA>폐업 등20121022<NA><NA><NA>경기도 화성시 동부대로1120번가길 3경기도 화성시 오산동 967-275번지44515037.202804127.091498<NA><NA><NA>식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>
416화성시다래물산20050311<NA><NA>폐업 등20090302<NA><NA><NA>경기도 화성시 기산로 35경기도 화성시 기산동 295-7번지44530037.220343127.045418<NA><NA><NA>식품냉동.냉장업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA>