Overview

Dataset statistics

Number of variables53
Number of observations10000
Missing cells204970
Missing cells (%)38.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 MiB
Average record size in memory468.0 B

Variable types

Numeric27
Categorical17
Text8
Unsupported1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-13663/S/1/datasetView.do

Alerts

년도 has constant value ""Constant
모범음식점여부 has constant value ""Constant
지하_부터 is highly imbalanced (80.9%)Imbalance
지하_까지 is highly imbalanced (81.0%)Imbalance
급수시설 is highly imbalanced (58.9%)Imbalance
종업원남 is highly imbalanced (99.4%)Imbalance
종업원여 is highly imbalanced (99.4%)Imbalance
급식소종류 is highly imbalanced (99.2%)Imbalance
운영형태 is highly imbalanced (96.7%)Imbalance
영업장무도장면적(㎡) is highly imbalanced (74.3%)Imbalance
영업장탈의실면적(㎡) is highly imbalanced (74.4%)Imbalance
검사실면적(㎡) is highly imbalanced (79.4%)Imbalance
내외국인구분 is highly imbalanced (90.2%)Imbalance
국적 is highly imbalanced (96.6%)Imbalance
영업장면적(㎡) has 9179 (91.8%) missing valuesMissing
법인명 has 6839 (68.4%) missing valuesMissing
법인번호 has 6839 (68.4%) missing valuesMissing
폐업일자 has 5808 (58.1%) missing valuesMissing
폐업사유 has 7332 (73.3%) missing valuesMissing
지상_부터 has 7877 (78.8%) missing valuesMissing
지상_까지 has 7950 (79.5%) missing valuesMissing
총층수 has 9185 (91.8%) missing valuesMissing
교육수료일자 has 10000 (100.0%) missing valuesMissing
평균급식인원수 has 9916 (99.2%) missing valuesMissing
최대급식인원수 has 9916 (99.2%) missing valuesMissing
1일급식인원수 has 9917 (99.2%) missing valuesMissing
일인당평균급식비 has 9916 (99.2%) missing valuesMissing
영업장조리장면적(㎡) has 7581 (75.8%) missing valuesMissing
영업장객실면적(㎡) has 9370 (93.7%) missing valuesMissing
영업장기타면적(㎡) has 6548 (65.5%) missing valuesMissing
업소내화장실면적(㎡) has 9005 (90.0%) missing valuesMissing
타업소공동화장실면적(㎡) has 9071 (90.7%) missing valuesMissing
영업장객석면적(㎡) has 8578 (85.8%) missing valuesMissing
작업장면적(㎡) has 8672 (86.7%) missing valuesMissing
진열(판매)대면적(㎡) has 9552 (95.5%) missing valuesMissing
창고(보관소)면적(㎡) has 9555 (95.5%) missing valuesMissing
조건부허가시작일 has 8182 (81.8%) missing valuesMissing
조건부허가종료일 has 8182 (81.8%) missing valuesMissing
허가신고일 is highly skewed (γ1 = -81.32253158)Skewed
소재지시작일 is highly skewed (γ1 = -30.63961545)Skewed
작업장면적(㎡) is highly skewed (γ1 = 36.3678222)Skewed
조건부허가시작일 is highly skewed (γ1 = 25.81748622)Skewed
교육수료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장조리장면적(㎡) has 222 (2.2%) zerosZeros
영업장객실면적(㎡) has 430 (4.3%) zerosZeros
영업장기타면적(㎡) has 510 (5.1%) zerosZeros
업소내화장실면적(㎡) has 811 (8.1%) zerosZeros
타업소공동화장실면적(㎡) has 827 (8.3%) zerosZeros
영업장객석면적(㎡) has 311 (3.1%) zerosZeros
작업장면적(㎡) has 270 (2.7%) zerosZeros
진열(판매)대면적(㎡) has 314 (3.1%) zerosZeros
창고(보관소)면적(㎡) has 391 (3.9%) zerosZeros

Reproduction

Analysis started2024-05-04 02:45:27.753222
Analysis finished2024-05-04 02:45:33.876132
Duration6.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3140897
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:45:34.118060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13080000
median3150000
Q33210000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)130000

Descriptive statistics

Standard deviation72806.562
Coefficient of variation (CV)0.023180181
Kurtosis-1.1180953
Mean3140897
Median Absolute Deviation (MAD)60000
Skewness-0.37680835
Sum3.140897 × 1010
Variance5.3007955 × 109
MonotonicityNot monotonic
2024-05-04T02:45:34.533368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 1059
 
10.6%
3230000 764
 
7.6%
3180000 634
 
6.3%
3150000 616
 
6.2%
3210000 587
 
5.9%
3130000 581
 
5.8%
3240000 410
 
4.1%
3200000 400
 
4.0%
3160000 349
 
3.5%
3030000 343
 
3.4%
Other values (15) 4257
42.6%
ValueCountFrequency (%)
3000000 228
2.3%
3010000 335
3.4%
3020000 277
2.8%
3030000 343
3.4%
3040000 327
3.3%
3050000 283
2.8%
3060000 257
2.6%
3070000 306
3.1%
3080000 310
3.1%
3090000 194
1.9%
ValueCountFrequency (%)
3240000 410
 
4.1%
3230000 764
7.6%
3220000 1059
10.6%
3210000 587
5.9%
3200000 400
 
4.0%
3190000 256
 
2.6%
3180000 634
6.3%
3170000 236
 
2.4%
3160000 349
 
3.5%
3150000 616
6.2%

업종코드
Real number (ℝ)

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.115
Minimum101
Maximum135
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:45:34.975997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1101
median107
Q3113
95-th percentile134
Maximum135
Range34
Interquartile range (IQR)12

Descriptive statistics

Standard deviation12.527485
Coefficient of variation (CV)0.11274341
Kurtosis-0.44966361
Mean111.115
Median Absolute Deviation (MAD)6
Skewness1.1231097
Sum1111150
Variance156.93787
MonotonicityNot monotonic
2024-05-04T02:45:35.516218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
101 3017
30.2%
107 2554
25.5%
134 1994
19.9%
104 1386
13.9%
113 342
 
3.4%
135 132
 
1.3%
112 130
 
1.3%
121 130
 
1.3%
105 88
 
0.9%
109 78
 
0.8%
Other values (9) 149
 
1.5%
ValueCountFrequency (%)
101 3017
30.2%
102 6
 
0.1%
103 2
 
< 0.1%
104 1386
13.9%
105 88
 
0.9%
106 26
 
0.3%
107 2554
25.5%
109 78
 
0.8%
112 130
 
1.3%
113 342
 
3.4%
ValueCountFrequency (%)
135 132
 
1.3%
134 1994
19.9%
122 16
 
0.2%
121 130
 
1.3%
120 77
 
0.8%
118 5
 
0.1%
117 7
 
0.1%
116 1
 
< 0.1%
114 9
 
0.1%
113 342
 
3.4%

년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 10000
100.0%

Length

2024-05-04T02:45:35.990591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:45:36.254165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 10000
100.0%

업소일련번호
Real number (ℝ)

Distinct468
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.3763
Minimum1
Maximum1577
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:45:36.627922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q121
median56
Q3107
95-th percentile247
Maximum1577
Range1576
Interquartile range (IQR)86

Descriptive statistics

Standard deviation87.622534
Coefficient of variation (CV)1.0901539
Kurtosis20.525483
Mean80.3763
Median Absolute Deviation (MAD)39
Skewness3.0482737
Sum803763
Variance7677.7085
MonotonicityNot monotonic
2024-05-04T02:45:37.162496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 249
 
2.5%
2 201
 
2.0%
3 182
 
1.8%
4 157
 
1.6%
5 137
 
1.4%
7 133
 
1.3%
6 127
 
1.3%
10 110
 
1.1%
8 106
 
1.1%
9 106
 
1.1%
Other values (458) 8492
84.9%
ValueCountFrequency (%)
1 249
2.5%
2 201
2.0%
3 182
1.8%
4 157
1.6%
5 137
1.4%
6 127
1.3%
7 133
1.3%
8 106
1.1%
9 106
1.1%
10 110
1.1%
ValueCountFrequency (%)
1577 1
< 0.1%
923 1
< 0.1%
908 1
< 0.1%
906 1
< 0.1%
833 1
< 0.1%
828 1
< 0.1%
827 1
< 0.1%
815 1
< 0.1%
814 1
< 0.1%
774 1
< 0.1%

업종명
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반음식점
3017 
즉석판매제조가공업
2554 
건강기능식품일반판매업
1994 
휴게음식점
1386 
유통전문판매업
342 
Other values (14)
707 

Length

Max length13
Median length11
Mean length7.4694
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row일반음식점
2nd row즉석판매제조가공업
3rd row집단급식소
4th row건강기능식품일반판매업
5th row건강기능식품일반판매업

Common Values

ValueCountFrequency (%)
일반음식점 3017
30.2%
즉석판매제조가공업 2554
25.5%
건강기능식품일반판매업 1994
19.9%
휴게음식점 1386
13.9%
유통전문판매업 342
 
3.4%
건강기능식품유통전문판매업 132
 
1.3%
식품자동판매기영업 130
 
1.3%
제과점영업 130
 
1.3%
집단급식소 88
 
0.9%
식품소분업 78
 
0.8%
Other values (9) 149
 
1.5%

Length

2024-05-04T02:45:38.005807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 3017
30.2%
즉석판매제조가공업 2554
25.5%
건강기능식품일반판매업 1994
19.9%
휴게음식점 1386
13.9%
유통전문판매업 342
 
3.4%
건강기능식품유통전문판매업 132
 
1.3%
식품자동판매기영업 130
 
1.3%
제과점영업 130
 
1.3%
집단급식소 88
 
0.9%
식품소분업 78
 
0.8%
Other values (9) 149
 
1.5%

허가신고일
Real number (ℝ)

SKEWED 

Distinct96
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210207
Minimum19980325
Maximum20210415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:45:38.603842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980325
5-th percentile20210107
Q120210127
median20210225
Q320210322
95-th percentile20210409
Maximum20210415
Range230090
Interquartile range (IQR)195

Descriptive statistics

Standard deviation2529.9257
Coefficient of variation (CV)0.0001251806
Kurtosis7064.3145
Mean20210207
Median Absolute Deviation (MAD)97
Skewness-81.322532
Sum2.0210207 × 1011
Variance6400524.3
MonotonicityNot monotonic
2024-05-04T02:45:39.168177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210302 244
 
2.4%
20210104 222
 
2.2%
20210315 197
 
2.0%
20210222 196
 
2.0%
20210405 184
 
1.8%
20210329 174
 
1.7%
20210223 170
 
1.7%
20210303 169
 
1.7%
20210330 166
 
1.7%
20210226 165
 
1.7%
Other values (86) 8113
81.1%
ValueCountFrequency (%)
19980325 1
 
< 0.1%
20110121 1
 
< 0.1%
20190426 1
 
< 0.1%
20200201 1
 
< 0.1%
20200217 1
 
< 0.1%
20200309 1
 
< 0.1%
20201026 1
 
< 0.1%
20201230 1
 
< 0.1%
20201231 2
 
< 0.1%
20210102 5
0.1%
ValueCountFrequency (%)
20210415 32
 
0.3%
20210414 143
1.4%
20210413 135
1.4%
20210412 136
1.4%
20210409 128
1.3%
20210408 131
1.3%
20210407 116
1.2%
20210406 157
1.6%
20210405 184
1.8%
20210403 1
 
< 0.1%
Distinct8425
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T02:45:40.050467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length35
Mean length7.8004
Min length1

Characters and Unicode

Total characters78004
Distinct characters1115
Distinct categories16 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7713 ?
Unique (%)77.1%

Sample

1st row신월
2nd row핸드맘
3rd row은빛 어린이집
4th row다경잡화점
5th row박유림상사
ValueCountFrequency (%)
주식회사 572
 
4.0%
한시적영업 129
 
0.9%
세븐일레븐 68
 
0.5%
씨유 58
 
0.4%
카페 50
 
0.3%
gs25 46
 
0.3%
월드푸드 45
 
0.3%
명류당티에프 42
 
0.3%
coffee 35
 
0.2%
주)마켓인 32
 
0.2%
Other values (9699) 13337
92.5%
2024-05-04T02:45:41.184144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4418
 
5.7%
) 2095
 
2.7%
( 2083
 
2.7%
2074
 
2.7%
1876
 
2.4%
1845
 
2.4%
1689
 
2.2%
1161
 
1.5%
1067
 
1.4%
1031
 
1.3%
Other values (1105) 58665
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61527
78.9%
Space Separator 4418
 
5.7%
Lowercase Letter 3350
 
4.3%
Uppercase Letter 3112
 
4.0%
Close Punctuation 2096
 
2.7%
Open Punctuation 2084
 
2.7%
Decimal Number 1044
 
1.3%
Other Punctuation 249
 
0.3%
Dash Punctuation 103
 
0.1%
Math Symbol 6
 
< 0.1%
Other values (6) 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2074
 
3.4%
1876
 
3.0%
1845
 
3.0%
1689
 
2.7%
1161
 
1.9%
1067
 
1.7%
1031
 
1.7%
901
 
1.5%
809
 
1.3%
792
 
1.3%
Other values (1015) 48282
78.5%
Uppercase Letter
ValueCountFrequency (%)
E 275
 
8.8%
S 257
 
8.3%
C 221
 
7.1%
O 214
 
6.9%
A 185
 
5.9%
N 165
 
5.3%
B 159
 
5.1%
G 153
 
4.9%
T 147
 
4.7%
R 143
 
4.6%
Other values (16) 1193
38.3%
Lowercase Letter
ValueCountFrequency (%)
e 503
15.0%
o 328
 
9.8%
a 317
 
9.5%
i 193
 
5.8%
l 191
 
5.7%
n 190
 
5.7%
r 189
 
5.6%
t 160
 
4.8%
s 157
 
4.7%
f 126
 
3.8%
Other values (15) 996
29.7%
Other Punctuation
ValueCountFrequency (%)
& 123
49.4%
. 42
 
16.9%
, 29
 
11.6%
' 20
 
8.0%
17
 
6.8%
· 4
 
1.6%
: 4
 
1.6%
! 4
 
1.6%
? 3
 
1.2%
/ 2
 
0.8%
Decimal Number
ValueCountFrequency (%)
2 265
25.4%
5 162
15.5%
1 132
12.6%
4 95
 
9.1%
3 89
 
8.5%
9 73
 
7.0%
8 69
 
6.6%
0 64
 
6.1%
7 55
 
5.3%
6 40
 
3.8%
Math Symbol
ValueCountFrequency (%)
> 2
33.3%
< 2
33.3%
~ 1
16.7%
× 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 2095
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2083
> 99.9%
[ 1
 
< 0.1%
Control
ValueCountFrequency (%)
2
50.0%
2
50.0%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
4418
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61500
78.8%
Common 10013
 
12.8%
Latin 6463
 
8.3%
Han 28
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2074
 
3.4%
1876
 
3.1%
1845
 
3.0%
1689
 
2.7%
1161
 
1.9%
1067
 
1.7%
1031
 
1.7%
901
 
1.5%
809
 
1.3%
792
 
1.3%
Other values (993) 48255
78.5%
Latin
ValueCountFrequency (%)
e 503
 
7.8%
o 328
 
5.1%
a 317
 
4.9%
E 275
 
4.3%
S 257
 
4.0%
C 221
 
3.4%
O 214
 
3.3%
i 193
 
3.0%
l 191
 
3.0%
n 190
 
2.9%
Other values (42) 3774
58.4%
Common
ValueCountFrequency (%)
4418
44.1%
) 2095
20.9%
( 2083
20.8%
2 265
 
2.6%
5 162
 
1.6%
1 132
 
1.3%
& 123
 
1.2%
- 103
 
1.0%
4 95
 
0.9%
3 89
 
0.9%
Other values (27) 448
 
4.5%
Han
ValueCountFrequency (%)
3
 
10.7%
2
 
7.1%
2
 
7.1%
2
 
7.1%
1
 
3.6%
1
 
3.6%
1
 
3.6%
1
 
3.6%
1
 
3.6%
1
 
3.6%
Other values (13) 13
46.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61493
78.8%
ASCII 16451
 
21.1%
CJK 25
 
< 0.1%
None 24
 
< 0.1%
Compat Jamo 6
 
< 0.1%
CJK Compat Ideographs 3
 
< 0.1%
Number Forms 1
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4418
26.9%
) 2095
 
12.7%
( 2083
 
12.7%
e 503
 
3.1%
o 328
 
2.0%
a 317
 
1.9%
E 275
 
1.7%
2 265
 
1.6%
S 257
 
1.6%
C 221
 
1.3%
Other values (73) 5689
34.6%
Hangul
ValueCountFrequency (%)
2074
 
3.4%
1876
 
3.1%
1845
 
3.0%
1689
 
2.7%
1161
 
1.9%
1067
 
1.7%
1031
 
1.7%
901
 
1.5%
809
 
1.3%
792
 
1.3%
Other values (989) 48248
78.5%
None
ValueCountFrequency (%)
17
70.8%
· 4
 
16.7%
1
 
4.2%
² 1
 
4.2%
× 1
 
4.2%
CJK Compat Ideographs
ValueCountFrequency (%)
3
100.0%
Compat Jamo
ValueCountFrequency (%)
3
50.0%
2
33.3%
1
 
16.7%
CJK
ValueCountFrequency (%)
2
 
8.0%
2
 
8.0%
2
 
8.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
Other values (12) 12
48.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Distinct8384
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T02:45:42.079267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length60
Mean length36.8915
Min length23

Characters and Unicode

Total characters368915
Distinct characters673
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7843 ?
Unique (%)78.4%

Sample

1st row서울특별시 성동구 연무장길 5-9, 1,2층 (성수동2가)
2nd row서울특별시 관악구 청림3길 10, 지하1층 (봉천동, 서희스타힐즈)
3rd row서울특별시 송파구 삼전로4길 4, (삼전동)
4th row서울특별시 마포구 숭문길 106, 101동 1109호 (염리동, 상록아파트)
5th row서울특별시 은평구 은평로10길 25-1, 1층 우측호 (응암동)
ValueCountFrequency (%)
서울특별시 10000
 
13.9%
1층 3491
 
4.9%
지하1층 1586
 
2.2%
강남구 1059
 
1.5%
송파구 764
 
1.1%
2층 746
 
1.0%
영등포구 634
 
0.9%
강서구 616
 
0.9%
서초구 587
 
0.8%
마포구 581
 
0.8%
Other values (10151) 51639
72.0%
2024-05-04T02:45:43.534640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61746
 
16.7%
1 18451
 
5.0%
13631
 
3.7%
12620
 
3.4%
, 12389
 
3.4%
10887
 
3.0%
10858
 
2.9%
10533
 
2.9%
10243
 
2.8%
) 10132
 
2.7%
Other values (663) 197425
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 212204
57.5%
Space Separator 61746
 
16.7%
Decimal Number 58758
 
15.9%
Other Punctuation 12419
 
3.4%
Close Punctuation 10132
 
2.7%
Open Punctuation 10132
 
2.7%
Uppercase Letter 1642
 
0.4%
Dash Punctuation 1561
 
0.4%
Lowercase Letter 215
 
0.1%
Math Symbol 65
 
< 0.1%
Other values (4) 41
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13631
 
6.4%
12620
 
5.9%
10887
 
5.1%
10858
 
5.1%
10533
 
5.0%
10243
 
4.8%
10004
 
4.7%
10004
 
4.7%
8112
 
3.8%
5157
 
2.4%
Other values (586) 110155
51.9%
Uppercase Letter
ValueCountFrequency (%)
B 430
26.2%
A 163
 
9.9%
C 144
 
8.8%
S 119
 
7.2%
N 80
 
4.9%
E 80
 
4.9%
G 74
 
4.5%
T 69
 
4.2%
K 61
 
3.7%
R 60
 
3.7%
Other values (16) 362
22.0%
Lowercase Letter
ValueCountFrequency (%)
e 41
19.1%
a 21
9.8%
n 19
8.8%
b 19
8.8%
s 17
7.9%
c 15
 
7.0%
i 12
 
5.6%
o 10
 
4.7%
r 10
 
4.7%
t 10
 
4.7%
Other values (12) 41
19.1%
Decimal Number
ValueCountFrequency (%)
1 18451
31.4%
2 8552
14.6%
0 6274
 
10.7%
3 5712
 
9.7%
4 4241
 
7.2%
5 3970
 
6.8%
6 3619
 
6.2%
7 2939
 
5.0%
8 2615
 
4.5%
9 2385
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 12389
99.8%
. 16
 
0.1%
& 8
 
0.1%
/ 5
 
< 0.1%
: 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
21
65.6%
7
 
21.9%
3
 
9.4%
1
 
3.1%
Math Symbol
ValueCountFrequency (%)
~ 64
98.5%
+ 1
 
1.5%
Control
ValueCountFrequency (%)
2
50.0%
2
50.0%
Space Separator
ValueCountFrequency (%)
61746
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10132
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10132
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1561
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 212208
57.5%
Common 154818
42.0%
Latin 1889
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13631
 
6.4%
12620
 
5.9%
10887
 
5.1%
10858
 
5.1%
10533
 
5.0%
10243
 
4.8%
10004
 
4.7%
10004
 
4.7%
8112
 
3.8%
5157
 
2.4%
Other values (587) 110159
51.9%
Latin
ValueCountFrequency (%)
B 430
22.8%
A 163
 
8.6%
C 144
 
7.6%
S 119
 
6.3%
N 80
 
4.2%
E 80
 
4.2%
G 74
 
3.9%
T 69
 
3.7%
K 61
 
3.2%
R 60
 
3.2%
Other values (42) 609
32.2%
Common
ValueCountFrequency (%)
61746
39.9%
1 18451
 
11.9%
, 12389
 
8.0%
) 10132
 
6.5%
( 10132
 
6.5%
2 8552
 
5.5%
0 6274
 
4.1%
3 5712
 
3.7%
4 4241
 
2.7%
5 3970
 
2.6%
Other values (14) 13219
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 212204
57.5%
ASCII 156675
42.5%
Number Forms 32
 
< 0.1%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
61746
39.4%
1 18451
 
11.8%
, 12389
 
7.9%
) 10132
 
6.5%
( 10132
 
6.5%
2 8552
 
5.5%
0 6274
 
4.0%
3 5712
 
3.6%
4 4241
 
2.7%
5 3970
 
2.5%
Other values (62) 15076
 
9.6%
Hangul
ValueCountFrequency (%)
13631
 
6.4%
12620
 
5.9%
10887
 
5.1%
10858
 
5.1%
10533
 
5.0%
10243
 
4.8%
10004
 
4.7%
10004
 
4.7%
8112
 
3.8%
5157
 
2.4%
Other values (586) 110155
51.9%
Number Forms
ValueCountFrequency (%)
21
65.6%
7
 
21.9%
3
 
9.4%
1
 
3.1%
None
ValueCountFrequency (%)
4
100.0%
Distinct7028
Distinct (%)70.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T02:45:44.289777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length54
Mean length29.5739
Min length19

Characters and Unicode

Total characters295739
Distinct characters641
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6148 ?
Unique (%)61.5%

Sample

1st row서울특별시 성동구 성수동2가 301번지 61호
2nd row서울특별시 관악구 봉천동 1729번지 서희스타힐즈
3rd row서울특별시 송파구 삼전동 35번지
4th row서울특별시 마포구 염리동 515번지 1호 101 상록아파트-1109
5th row서울특별시 은평구 응암동 100번지 45호
ValueCountFrequency (%)
서울특별시 10000
 
17.8%
강남구 1059
 
1.9%
1호 862
 
1.5%
송파구 764
 
1.4%
영등포구 634
 
1.1%
강서구 616
 
1.1%
서초구 587
 
1.0%
마포구 581
 
1.0%
2호 533
 
0.9%
1층 489
 
0.9%
Other values (5767) 40187
71.4%
2024-05-04T02:45:45.510427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
69627
23.5%
12078
 
4.1%
11621
 
3.9%
10768
 
3.6%
10668
 
3.6%
10397
 
3.5%
10111
 
3.4%
10090
 
3.4%
10003
 
3.4%
10003
 
3.4%
Other values (631) 130373
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 178181
60.2%
Space Separator 69627
 
23.5%
Decimal Number 45379
 
15.3%
Uppercase Letter 1163
 
0.4%
Dash Punctuation 703
 
0.2%
Lowercase Letter 200
 
0.1%
Other Punctuation 184
 
0.1%
Close Punctuation 126
 
< 0.1%
Open Punctuation 126
 
< 0.1%
Letter Number 32
 
< 0.1%
Other values (2) 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12078
 
6.8%
11621
 
6.5%
10768
 
6.0%
10668
 
6.0%
10397
 
5.8%
10111
 
5.7%
10090
 
5.7%
10003
 
5.6%
10003
 
5.6%
7955
 
4.5%
Other values (556) 74487
41.8%
Uppercase Letter
ValueCountFrequency (%)
C 116
 
10.0%
B 105
 
9.0%
E 90
 
7.7%
N 88
 
7.6%
A 84
 
7.2%
S 82
 
7.1%
T 76
 
6.5%
K 73
 
6.3%
I 63
 
5.4%
M 53
 
4.6%
Other values (16) 333
28.6%
Lowercase Letter
ValueCountFrequency (%)
e 47
23.5%
n 17
 
8.5%
o 16
 
8.0%
r 15
 
7.5%
s 13
 
6.5%
a 12
 
6.0%
i 12
 
6.0%
t 12
 
6.0%
c 11
 
5.5%
l 9
 
4.5%
Other values (13) 36
18.0%
Decimal Number
ValueCountFrequency (%)
1 9738
21.5%
2 6179
13.6%
3 4938
10.9%
4 4206
9.3%
5 3866
 
8.5%
6 3826
 
8.4%
0 3533
 
7.8%
7 3394
 
7.5%
9 3053
 
6.7%
8 2646
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 167
90.8%
& 8
 
4.3%
. 6
 
3.3%
: 1
 
0.5%
' 1
 
0.5%
/ 1
 
0.5%
Letter Number
ValueCountFrequency (%)
21
65.6%
7
 
21.9%
3
 
9.4%
1
 
3.1%
Space Separator
ValueCountFrequency (%)
69627
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 703
100.0%
Close Punctuation
ValueCountFrequency (%)
) 126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 178185
60.3%
Common 116159
39.3%
Latin 1395
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12078
 
6.8%
11621
 
6.5%
10768
 
6.0%
10668
 
6.0%
10397
 
5.8%
10111
 
5.7%
10090
 
5.7%
10003
 
5.6%
10003
 
5.6%
7955
 
4.5%
Other values (557) 74491
41.8%
Latin
ValueCountFrequency (%)
C 116
 
8.3%
B 105
 
7.5%
E 90
 
6.5%
N 88
 
6.3%
A 84
 
6.0%
S 82
 
5.9%
T 76
 
5.4%
K 73
 
5.2%
I 63
 
4.5%
M 53
 
3.8%
Other values (43) 565
40.5%
Common
ValueCountFrequency (%)
69627
59.9%
1 9738
 
8.4%
2 6179
 
5.3%
3 4938
 
4.3%
4 4206
 
3.6%
5 3866
 
3.3%
6 3826
 
3.3%
0 3533
 
3.0%
7 3394
 
2.9%
9 3053
 
2.6%
Other values (11) 3799
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 178181
60.2%
ASCII 117522
39.7%
Number Forms 32
 
< 0.1%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
69627
59.2%
1 9738
 
8.3%
2 6179
 
5.3%
3 4938
 
4.2%
4 4206
 
3.6%
5 3866
 
3.3%
6 3826
 
3.3%
0 3533
 
3.0%
7 3394
 
2.9%
9 3053
 
2.6%
Other values (60) 5162
 
4.4%
Hangul
ValueCountFrequency (%)
12078
 
6.8%
11621
 
6.5%
10768
 
6.0%
10668
 
6.0%
10397
 
5.8%
10111
 
5.7%
10090
 
5.7%
10003
 
5.6%
10003
 
5.6%
7955
 
4.5%
Other values (556) 74487
41.8%
Number Forms
ValueCountFrequency (%)
21
65.6%
7
 
21.9%
3
 
9.4%
1
 
3.1%
None
ValueCountFrequency (%)
4
100.0%

영업장면적(㎡)
Real number (ℝ)

MISSING 

Distinct508
Distinct (%)61.9%
Missing9179
Missing (%)91.8%
Infinite0
Infinite (%)0.0%
Mean62.017929
Minimum0
Maximum1570.41
Zeros26
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:45:46.028166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.65
Q114.24
median30
Q360
95-th percentile228.06
Maximum1570.41
Range1570.41
Interquartile range (IQR)45.76

Descriptive statistics

Standard deviation116.75667
Coefficient of variation (CV)1.8826276
Kurtosis73.335841
Mean62.017929
Median Absolute Deviation (MAD)19.96
Skewness7.0022602
Sum50916.72
Variance13632.119
MonotonicityNot monotonic
2024-05-04T02:45:46.680222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 26
 
0.3%
10.0 21
 
0.2%
3.3 18
 
0.2%
6.6 17
 
0.2%
20.0 17
 
0.2%
30.0 16
 
0.2%
1.0 13
 
0.1%
18.0 11
 
0.1%
40.0 10
 
0.1%
16.5 9
 
0.1%
Other values (498) 663
 
6.6%
(Missing) 9179
91.8%
ValueCountFrequency (%)
0.0 26
0.3%
1.0 13
0.1%
1.3 1
 
< 0.1%
1.65 2
 
< 0.1%
2.0 1
 
< 0.1%
2.5 1
 
< 0.1%
2.6 1
 
< 0.1%
2.98 1
 
< 0.1%
3.0 6
 
0.1%
3.3 18
0.2%
ValueCountFrequency (%)
1570.41 1
< 0.1%
1570.3 1
< 0.1%
850.16 1
< 0.1%
680.38 1
< 0.1%
657.36 1
< 0.1%
565.43 1
< 0.1%
555.64 1
< 0.1%
550.8 1
< 0.1%
537.9 1
< 0.1%
525.47 1
< 0.1%

영업자시작일
Real number (ℝ)

Distinct496
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20211157
Minimum19980325
Maximum20230324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:45:47.268255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980325
5-th percentile20210107
Q120210201
median20210303
Q320210330
95-th percentile20220523
Maximum20230324
Range249999
Interquartile range (IQR)129

Descriptive statistics

Standard deviation4427.295
Coefficient of variation (CV)0.00021905203
Kurtosis772.47559
Mean20211157
Median Absolute Deviation (MAD)99
Skewness-13.129794
Sum2.0211157 × 1011
Variance19600941
MonotonicityNot monotonic
2024-05-04T02:45:47.841866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210302 220
 
2.2%
20210104 196
 
2.0%
20210315 179
 
1.8%
20210222 178
 
1.8%
20210329 168
 
1.7%
20210405 166
 
1.7%
20210303 157
 
1.6%
20210330 154
 
1.5%
20210331 150
 
1.5%
20210118 149
 
1.5%
Other values (486) 8283
82.8%
ValueCountFrequency (%)
19980325 1
 
< 0.1%
20110121 1
 
< 0.1%
20190426 1
 
< 0.1%
20200201 1
 
< 0.1%
20200217 1
 
< 0.1%
20200309 1
 
< 0.1%
20201026 1
 
< 0.1%
20201230 1
 
< 0.1%
20201231 2
 
< 0.1%
20210102 5
0.1%
ValueCountFrequency (%)
20230324 2
 
< 0.1%
20230322 6
0.1%
20230321 5
0.1%
20230320 4
 
< 0.1%
20230317 2
 
< 0.1%
20230316 5
0.1%
20230315 11
0.1%
20230314 2
 
< 0.1%
20230313 5
0.1%
20230310 3
 
< 0.1%

법인명
Text

MISSING 

Distinct1802
Distinct (%)57.0%
Missing6839
Missing (%)68.4%
Memory size156.2 KiB
2024-05-04T02:45:48.788316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length9.4795951
Min length2

Characters and Unicode

Total characters29965
Distinct characters665
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1388 ?
Unique (%)43.9%

Sample

1st row(주)수에프앤비
2nd row(주)한국생활건강
3rd row에이치제이에프
4th row주식회사 마켓인
5th row주식회사 마켓인
ValueCountFrequency (%)
주식회사 2108
39.0%
월드푸드 54
 
1.0%
네이쳐키친 50
 
0.9%
명류당티에프 40
 
0.7%
마켓인 37
 
0.7%
씨엔 27
 
0.5%
농촌사랑 25
 
0.5%
유한회사 24
 
0.4%
신세계푸드 23
 
0.4%
행복생활건강 22
 
0.4%
Other values (1784) 2999
55.4%
2024-05-04T02:45:50.521735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2911
 
9.7%
2407
 
8.0%
2324
 
7.8%
2283
 
7.6%
2249
 
7.5%
816
 
2.7%
) 686
 
2.3%
( 686
 
2.3%
651
 
2.2%
650
 
2.2%
Other values (655) 14302
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26178
87.4%
Space Separator 2249
 
7.5%
Close Punctuation 686
 
2.3%
Open Punctuation 686
 
2.3%
Uppercase Letter 73
 
0.2%
Lowercase Letter 44
 
0.1%
Decimal Number 29
 
0.1%
Other Punctuation 15
 
0.1%
Other Symbol 2
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2911
 
11.1%
2407
 
9.2%
2324
 
8.9%
2283
 
8.7%
816
 
3.1%
651
 
2.5%
650
 
2.5%
649
 
2.5%
449
 
1.7%
426
 
1.6%
Other values (605) 12612
48.2%
Uppercase Letter
ValueCountFrequency (%)
C 10
13.7%
L 8
11.0%
R 7
9.6%
I 6
 
8.2%
E 5
 
6.8%
T 5
 
6.8%
B 4
 
5.5%
A 4
 
5.5%
S 4
 
5.5%
O 4
 
5.5%
Other values (10) 16
21.9%
Lowercase Letter
ValueCountFrequency (%)
a 6
13.6%
t 5
11.4%
d 4
9.1%
o 4
9.1%
e 4
9.1%
n 3
6.8%
c 3
6.8%
f 3
6.8%
l 3
6.8%
u 2
 
4.5%
Other values (4) 7
15.9%
Decimal Number
ValueCountFrequency (%)
2 9
31.0%
1 5
17.2%
0 4
13.8%
3 4
13.8%
9 3
 
10.3%
5 2
 
6.9%
4 2
 
6.9%
Other Punctuation
ValueCountFrequency (%)
. 9
60.0%
, 5
33.3%
& 1
 
6.7%
Space Separator
ValueCountFrequency (%)
2249
100.0%
Close Punctuation
ValueCountFrequency (%)
) 686
100.0%
Open Punctuation
ValueCountFrequency (%)
( 686
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26178
87.4%
Common 3668
 
12.2%
Latin 117
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2911
 
11.1%
2407
 
9.2%
2324
 
8.9%
2283
 
8.7%
816
 
3.1%
651
 
2.5%
650
 
2.5%
649
 
2.5%
449
 
1.7%
426
 
1.6%
Other values (604) 12612
48.2%
Latin
ValueCountFrequency (%)
C 10
 
8.5%
L 8
 
6.8%
R 7
 
6.0%
I 6
 
5.1%
a 6
 
5.1%
t 5
 
4.3%
E 5
 
4.3%
T 5
 
4.3%
B 4
 
3.4%
A 4
 
3.4%
Other values (24) 57
48.7%
Common
ValueCountFrequency (%)
2249
61.3%
) 686
 
18.7%
( 686
 
18.7%
2 9
 
0.2%
. 9
 
0.2%
, 5
 
0.1%
1 5
 
0.1%
0 4
 
0.1%
3 4
 
0.1%
9 3
 
0.1%
Other values (5) 8
 
0.2%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26176
87.4%
ASCII 3785
 
12.6%
None 2
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2911
 
11.1%
2407
 
9.2%
2324
 
8.9%
2283
 
8.7%
816
 
3.1%
651
 
2.5%
650
 
2.5%
649
 
2.5%
449
 
1.7%
426
 
1.6%
Other values (603) 12610
48.2%
ASCII
ValueCountFrequency (%)
2249
59.4%
) 686
 
18.1%
( 686
 
18.1%
C 10
 
0.3%
2 9
 
0.2%
. 9
 
0.2%
L 8
 
0.2%
R 7
 
0.2%
I 6
 
0.2%
a 6
 
0.2%
Other values (39) 109
 
2.9%
None
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

법인번호
Real number (ℝ)

MISSING 

Distinct1573
Distinct (%)49.8%
Missing6839
Missing (%)68.4%
Infinite0
Infinite (%)0.0%
Mean1.2884996 × 1012
Minimum1.5482004 × 109
Maximum9.0042211 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:45:51.244046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5482004 × 109
5-th percentile1.1011111 × 1012
Q11.1011154 × 1012
median1.1011176 × 1012
Q31.3141104 × 1012
95-th percentile2.11311 × 1012
Maximum9.0042211 × 1012
Range9.0026729 × 1012
Interquartile range (IQR)2.1299501 × 1011

Descriptive statistics

Standard deviation4.5639796 × 1011
Coefficient of variation (CV)0.35420885
Kurtosis50.327647
Mean1.2884996 × 1012
Median Absolute Deviation (MAD)3675088
Skewness5.0036265
Sum4.0729472 × 1015
Variance2.0829909 × 1023
MonotonicityNot monotonic
2024-05-04T02:45:52.048339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1101117780508 64
 
0.6%
1101113441477 59
 
0.6%
1201110572463 53
 
0.5%
1101110899976 39
 
0.4%
2850110435532 39
 
0.4%
1101110305288 35
 
0.4%
1357110090177 27
 
0.3%
1101115423796 26
 
0.3%
1101114490449 25
 
0.2%
2001110344815 24
 
0.2%
Other values (1563) 2770
27.7%
(Missing) 6839
68.4%
ValueCountFrequency (%)
1548200400 1
 
< 0.1%
1828001638 1
 
< 0.1%
2068271899 1
 
< 0.1%
3518300027 1
 
< 0.1%
1088207924111 1
 
< 0.1%
1101110000086 3
< 0.1%
1101110003098 6
0.1%
1101110006852 6
0.1%
1101110013328 1
 
< 0.1%
1101110033376 1
 
< 0.1%
ValueCountFrequency (%)
9004221059412 1
 
< 0.1%
7906302069015 1
 
< 0.1%
6605181558811 1
 
< 0.1%
5018267970111 1
 
< 0.1%
2850110465688 1
 
< 0.1%
2850110449567 1
 
< 0.1%
2850110435532 39
0.4%
2850110422092 1
 
< 0.1%
2850110400527 2
 
< 0.1%
2850110377966 1
 
< 0.1%

소재지시작일
Real number (ℝ)

SKEWED 

Distinct425
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210650
Minimum19980325
Maximum20230324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:45:52.647176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980325
5-th percentile20210107
Q120210129
median20210302
Q320210326
95-th percentile20210622
Maximum20230324
Range249999
Interquartile range (IQR)197

Descriptive statistics

Standard deviation3442.6923
Coefficient of variation (CV)0.0001703405
Kurtosis2083.187
Mean20210650
Median Absolute Deviation (MAD)97
Skewness-30.639615
Sum2.021065 × 1011
Variance11852130
MonotonicityNot monotonic
2024-05-04T02:45:53.269981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210302 235
 
2.4%
20210104 205
 
2.1%
20210222 184
 
1.8%
20210315 183
 
1.8%
20210405 177
 
1.8%
20210329 163
 
1.6%
20210303 163
 
1.6%
20210223 162
 
1.6%
20210226 162
 
1.6%
20210330 160
 
1.6%
Other values (415) 8206
82.1%
ValueCountFrequency (%)
19980325 1
 
< 0.1%
20110121 1
 
< 0.1%
20190426 1
 
< 0.1%
20200201 1
 
< 0.1%
20200217 1
 
< 0.1%
20201026 1
 
< 0.1%
20201230 1
 
< 0.1%
20201231 1
 
< 0.1%
20210102 5
 
0.1%
20210104 205
2.1%
ValueCountFrequency (%)
20230324 1
 
< 0.1%
20230322 4
< 0.1%
20230316 1
 
< 0.1%
20230314 1
 
< 0.1%
20230313 2
< 0.1%
20230310 2
< 0.1%
20230309 1
 
< 0.1%
20230306 4
< 0.1%
20230302 2
< 0.1%
20230227 2
< 0.1%
Distinct405
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T02:45:54.182100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length7
Mean length4.1474
Min length2

Characters and Unicode

Total characters41474
Distinct characters185
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)0.1%

Sample

1st row성수2가제1동
2nd row청림동
3rd row삼전동
4th row염리동
5th row응암제1동
ValueCountFrequency (%)
역삼1동 289
 
2.9%
여의동 227
 
2.3%
신사동 193
 
1.9%
논현1동 181
 
1.8%
문정1동 164
 
1.6%
서교동 159
 
1.6%
삼성1동 146
 
1.5%
가양제1동 136
 
1.4%
서초제1동 134
 
1.3%
영등포동 116
 
1.2%
Other values (395) 8255
82.5%
2024-05-04T02:45:55.479225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10023
24.2%
3944
 
9.5%
1 3796
 
9.2%
2 1278
 
3.1%
843
 
2.0%
702
 
1.7%
3 589
 
1.4%
534
 
1.3%
491
 
1.2%
459
 
1.1%
Other values (175) 18815
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34790
83.9%
Decimal Number 6430
 
15.5%
Other Punctuation 254
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10023
28.8%
3944
 
11.3%
843
 
2.4%
702
 
2.0%
534
 
1.5%
491
 
1.4%
459
 
1.3%
447
 
1.3%
445
 
1.3%
407
 
1.2%
Other values (164) 16495
47.4%
Decimal Number
ValueCountFrequency (%)
1 3796
59.0%
2 1278
 
19.9%
3 589
 
9.2%
4 421
 
6.5%
5 136
 
2.1%
6 87
 
1.4%
7 58
 
0.9%
8 40
 
0.6%
9 18
 
0.3%
0 7
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 254
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34790
83.9%
Common 6684
 
16.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10023
28.8%
3944
 
11.3%
843
 
2.4%
702
 
2.0%
534
 
1.5%
491
 
1.4%
459
 
1.3%
447
 
1.3%
445
 
1.3%
407
 
1.2%
Other values (164) 16495
47.4%
Common
ValueCountFrequency (%)
1 3796
56.8%
2 1278
 
19.1%
3 589
 
8.8%
4 421
 
6.3%
. 254
 
3.8%
5 136
 
2.0%
6 87
 
1.3%
7 58
 
0.9%
8 40
 
0.6%
9 18
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34790
83.9%
ASCII 6684
 
16.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
10023
28.8%
3944
 
11.3%
843
 
2.4%
702
 
2.0%
534
 
1.5%
491
 
1.4%
459
 
1.3%
447
 
1.3%
445
 
1.3%
407
 
1.2%
Other values (164) 16495
47.4%
ASCII
ValueCountFrequency (%)
1 3796
56.8%
2 1278
 
19.1%
3 589
 
8.8%
4 421
 
6.3%
. 254
 
3.8%
5 136
 
2.0%
6 87
 
1.3%
7 58
 
0.9%
8 40
 
0.6%
9 18
 
0.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct591
Distinct (%)14.1%
Missing5808
Missing (%)58.1%
Infinite0
Infinite (%)0.0%
Mean20215105
Minimum20210105
Maximum20230324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:45:55.937598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210105
5-th percentile20210128
Q120210321
median20210714
Q320220627
95-th percentile20230127
Maximum20230324
Range20219
Interquartile range (IQR)10306

Descriptive statistics

Standard deviation6344.0281
Coefficient of variation (CV)0.00031382613
Kurtosis-0.21399852
Mean20215105
Median Absolute Deviation (MAD)500
Skewness0.98372599
Sum8.474172 × 1010
Variance40246693
MonotonicityNot monotonic
2024-05-04T02:45:56.530803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210331 99
 
1.0%
20210414 65
 
0.7%
20210317 60
 
0.6%
20210325 49
 
0.5%
20210428 44
 
0.4%
20210303 43
 
0.4%
20210217 42
 
0.4%
20210430 41
 
0.4%
20210225 40
 
0.4%
20210304 39
 
0.4%
Other values (581) 3670
36.7%
(Missing) 5808
58.1%
ValueCountFrequency (%)
20210105 1
 
< 0.1%
20210107 2
 
< 0.1%
20210108 3
 
< 0.1%
20210109 3
 
< 0.1%
20210110 2
 
< 0.1%
20210111 1
 
< 0.1%
20210112 3
 
< 0.1%
20210113 3
 
< 0.1%
20210114 24
0.2%
20210115 1
 
< 0.1%
ValueCountFrequency (%)
20230324 5
0.1%
20230323 2
 
< 0.1%
20230322 10
0.1%
20230321 4
 
< 0.1%
20230320 6
0.1%
20230317 2
 
< 0.1%
20230316 8
0.1%
20230315 4
 
< 0.1%
20230314 4
 
< 0.1%
20230313 8
0.1%

폐업구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5808 
자진폐업
2066 
기타
1798 
전출
 
305
행정처분
 
23

Length

Max length4
Median length4
Mean length3.5794
Min length2

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> 5808
58.1%
자진폐업 2066
 
20.7%
기타 1798
 
18.0%
전출 305
 
3.0%
행정처분 23
 
0.2%

Length

2024-05-04T02:45:56.991372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:45:57.388080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5808
58.1%
자진폐업 2066
 
20.7%
기타 1798
 
18.0%
전출 305
 
3.0%
행정처분 23
 
0.2%

폐업사유
Text

MISSING 

Distinct308
Distinct (%)11.5%
Missing7332
Missing (%)73.3%
Memory size156.2 KiB
2024-05-04T02:45:57.949055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length23
Mean length18.439655
Min length2

Characters and Unicode

Total characters49197
Distinct characters241
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique204 ?
Unique (%)7.6%

Sample

1st row조건부기간 완료에 따른 폐업처리(자동폐업)
2nd row조건부기간 완료에 따른 폐업처리(자동폐업)
3rd row조건부기간 완료에 따른 폐업처리(자동폐업)
4th row조건부기간 완료에 따른 폐업처리(자동폐업)
5th row조건부기간 완료에 따른 폐업처리(자동폐업)
ValueCountFrequency (%)
따른 1789
20.1%
조건부기간 1779
20.0%
완료에 1779
20.0%
폐업처리(자동폐업 1775
19.9%
전출처리됨 305
 
3.4%
서울특별시 203
 
2.3%
경기도 67
 
0.8%
사업부진 61
 
0.7%
자진폐업 50
 
0.6%
폐업 42
 
0.5%
Other values (363) 1057
11.9%
2024-05-04T02:45:59.084196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6236
 
12.7%
3945
 
8.0%
3696
 
7.5%
2099
 
4.3%
2087
 
4.2%
1915
 
3.9%
1890
 
3.8%
1869
 
3.8%
1841
 
3.7%
1817
 
3.7%
Other values (231) 21802
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39228
79.7%
Space Separator 6236
 
12.7%
Open Punctuation 1793
 
3.6%
Close Punctuation 1793
 
3.6%
Decimal Number 95
 
0.2%
Other Punctuation 39
 
0.1%
Control 8
 
< 0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3945
 
10.1%
3696
 
9.4%
2099
 
5.4%
2087
 
5.3%
1915
 
4.9%
1890
 
4.8%
1869
 
4.8%
1841
 
4.7%
1817
 
4.6%
1812
 
4.6%
Other values (210) 16257
41.4%
Decimal Number
ValueCountFrequency (%)
2 38
40.0%
0 19
20.0%
3 11
 
11.6%
7 7
 
7.4%
1 6
 
6.3%
8 4
 
4.2%
9 4
 
4.2%
4 2
 
2.1%
5 2
 
2.1%
6 2
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 35
89.7%
, 3
 
7.7%
: 1
 
2.6%
Open Punctuation
ValueCountFrequency (%)
( 1790
99.8%
[ 3
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 1790
99.8%
] 3
 
0.2%
Control
ValueCountFrequency (%)
4
50.0%
4
50.0%
Space Separator
ValueCountFrequency (%)
6236
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39228
79.7%
Common 9969
 
20.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3945
 
10.1%
3696
 
9.4%
2099
 
5.4%
2087
 
5.3%
1915
 
4.9%
1890
 
4.8%
1869
 
4.8%
1841
 
4.7%
1817
 
4.6%
1812
 
4.6%
Other values (210) 16257
41.4%
Common
ValueCountFrequency (%)
6236
62.6%
( 1790
 
18.0%
) 1790
 
18.0%
2 38
 
0.4%
. 35
 
0.4%
0 19
 
0.2%
3 11
 
0.1%
7 7
 
0.1%
1 6
 
0.1%
- 5
 
0.1%
Other values (11) 32
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39228
79.7%
ASCII 9969
 
20.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6236
62.6%
( 1790
 
18.0%
) 1790
 
18.0%
2 38
 
0.4%
. 35
 
0.4%
0 19
 
0.2%
3 11
 
0.1%
7 7
 
0.1%
1 6
 
0.1%
- 5
 
0.1%
Other values (11) 32
 
0.3%
Hangul
ValueCountFrequency (%)
3945
 
10.1%
3696
 
9.4%
2099
 
5.4%
2087
 
5.3%
1915
 
4.9%
1890
 
4.8%
1869
 
4.8%
1841
 
4.7%
1817
 
4.6%
1812
 
4.6%
Other values (210) 16257
41.4%
Distinct63
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T02:45:59.574792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length6.7479
Min length2

Characters and Unicode

Total characters67479
Distinct characters141
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

Unique3 ?
Unique (%)< 0.1%

Sample

1st row일식
2nd row즉석판매제조가공업
3rd row어린이집
4th row전자상거래(통신판매업)
5th row전자상거래(통신판매업)
ValueCountFrequency (%)
즉석판매제조가공업 2553
24.6%
전자상거래(통신판매업 1672
16.1%
기타 1157
11.1%
한식 1076
10.3%
커피숍 519
 
5.0%
유통전문판매업 342
 
3.3%
휴게음식점 335
 
3.2%
경양식 291
 
2.8%
영업장판매 252
 
2.4%
편의점 210
 
2.0%
Other values (54) 1990
19.1%
2024-05-04T02:46:00.483928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5455
 
8.1%
5363
 
7.9%
5349
 
7.9%
2817
 
4.2%
2784
 
4.1%
2714
 
4.0%
2585
 
3.8%
2579
 
3.8%
2553
 
3.8%
2553
 
3.8%
Other values (131) 32727
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63162
93.6%
Open Punctuation 1813
 
2.7%
Close Punctuation 1813
 
2.7%
Space Separator 397
 
0.6%
Other Punctuation 294
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5455
 
8.6%
5363
 
8.5%
5349
 
8.5%
2817
 
4.5%
2784
 
4.4%
2714
 
4.3%
2585
 
4.1%
2579
 
4.1%
2553
 
4.0%
2553
 
4.0%
Other values (125) 28410
45.0%
Other Punctuation
ValueCountFrequency (%)
/ 206
70.1%
, 82
 
27.9%
. 6
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 1813
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1813
100.0%
Space Separator
ValueCountFrequency (%)
397
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63162
93.6%
Common 4317
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5455
 
8.6%
5363
 
8.5%
5349
 
8.5%
2817
 
4.5%
2784
 
4.4%
2714
 
4.3%
2585
 
4.1%
2579
 
4.1%
2553
 
4.0%
2553
 
4.0%
Other values (125) 28410
45.0%
Common
ValueCountFrequency (%)
( 1813
42.0%
) 1813
42.0%
397
 
9.2%
/ 206
 
4.8%
, 82
 
1.9%
. 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63162
93.6%
ASCII 4317
 
6.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5455
 
8.6%
5363
 
8.5%
5349
 
8.5%
2817
 
4.5%
2784
 
4.4%
2714
 
4.3%
2585
 
4.1%
2579
 
4.1%
2553
 
4.0%
2553
 
4.0%
Other values (125) 28410
45.0%
ASCII
ValueCountFrequency (%)
( 1813
42.0%
) 1813
42.0%
397
 
9.2%
/ 206
 
4.8%
, 82
 
1.9%
. 6
 
0.1%

지상_부터
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)0.7%
Missing7877
Missing (%)78.8%
Infinite0
Infinite (%)0.0%
Mean1.2195007
Minimum0
Maximum17
Zeros65
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:00.842252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum17
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.97221355
Coefficient of variation (CV)0.79722262
Kurtosis84.653683
Mean1.2195007
Median Absolute Deviation (MAD)0
Skewness7.4895806
Sum2589
Variance0.94519919
MonotonicityNot monotonic
2024-05-04T02:46:01.215550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 1766
 
17.7%
2 207
 
2.1%
0 65
 
0.7%
3 29
 
0.3%
4 24
 
0.2%
5 15
 
0.1%
6 8
 
0.1%
10 3
 
< 0.1%
15 1
 
< 0.1%
17 1
 
< 0.1%
Other values (4) 4
 
< 0.1%
(Missing) 7877
78.8%
ValueCountFrequency (%)
0 65
 
0.7%
1 1766
17.7%
2 207
 
2.1%
3 29
 
0.3%
4 24
 
0.2%
5 15
 
0.1%
6 8
 
0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
10 3
 
< 0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
15 1
 
< 0.1%
14 1
 
< 0.1%
11 1
 
< 0.1%
10 3
 
< 0.1%
9 1
 
< 0.1%
7 1
 
< 0.1%
6 8
 
0.1%
5 15
0.1%
4 24
0.2%

지상_까지
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)0.6%
Missing7950
Missing (%)79.5%
Infinite0
Infinite (%)0.0%
Mean1.2439024
Minimum0
Maximum18
Zeros66
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:01.592088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.97254873
Coefficient of variation (CV)0.7818529
Kurtosis77.496296
Mean1.2439024
Median Absolute Deviation (MAD)0
Skewness6.8795094
Sum2550
Variance0.94585104
MonotonicityNot monotonic
2024-05-04T02:46:02.179818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 1664
 
16.6%
2 224
 
2.2%
0 66
 
0.7%
3 38
 
0.4%
4 25
 
0.2%
5 16
 
0.2%
6 8
 
0.1%
10 3
 
< 0.1%
7 2
 
< 0.1%
18 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
(Missing) 7950
79.5%
ValueCountFrequency (%)
0 66
 
0.7%
1 1664
16.6%
2 224
 
2.2%
3 38
 
0.4%
4 25
 
0.2%
5 16
 
0.2%
6 8
 
0.1%
7 2
 
< 0.1%
9 1
 
< 0.1%
10 3
 
< 0.1%
ValueCountFrequency (%)
18 1
 
< 0.1%
14 1
 
< 0.1%
11 1
 
< 0.1%
10 3
 
< 0.1%
9 1
 
< 0.1%
7 2
 
< 0.1%
6 8
 
0.1%
5 16
0.2%
4 25
0.2%
3 38
0.4%

지하_부터
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9293 
1
 
544
0
 
79
2
 
75
3
 
9

Length

Max length4
Median length4
Mean length3.7879
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9293
92.9%
1 544
 
5.4%
0 79
 
0.8%
2 75
 
0.8%
3 9
 
0.1%

Length

2024-05-04T02:46:02.595972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:02.927566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9293
92.9%
1 544
 
5.4%
0 79
 
0.8%
2 75
 
0.8%
3 9
 
0.1%

지하_까지
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9302 
1
 
535
0
 
79
2
 
75
3
 
9

Length

Max length4
Median length4
Mean length3.7906
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9302
93.0%
1 535
 
5.3%
0 79
 
0.8%
2 75
 
0.8%
3 9
 
0.1%

Length

2024-05-04T02:46:03.314403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:03.646953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9302
93.0%
1 535
 
5.3%
0 79
 
0.8%
2 75
 
0.8%
3 9
 
0.1%

총층수
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)3.7%
Missing9185
Missing (%)91.8%
Infinite0
Infinite (%)0.0%
Mean6.5251534
Minimum0
Maximum49
Zeros80
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:03.982538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median5
Q38
95-th percentile19
Maximum49
Range49
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.0648861
Coefficient of variation (CV)0.92946261
Kurtosis6.1770196
Mean6.5251534
Median Absolute Deviation (MAD)2
Skewness1.9372083
Sum5318
Variance36.782843
MonotonicityNot monotonic
2024-05-04T02:46:04.378088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4 148
 
1.5%
5 119
 
1.2%
3 95
 
0.9%
0 80
 
0.8%
2 64
 
0.6%
6 42
 
0.4%
7 27
 
0.3%
9 26
 
0.3%
14 26
 
0.3%
8 22
 
0.2%
Other values (20) 166
 
1.7%
(Missing) 9185
91.8%
ValueCountFrequency (%)
0 80
0.8%
1 20
 
0.2%
2 64
0.6%
3 95
0.9%
4 148
1.5%
5 119
1.2%
6 42
 
0.4%
7 27
 
0.3%
8 22
 
0.2%
9 26
 
0.3%
ValueCountFrequency (%)
49 1
 
< 0.1%
48 1
 
< 0.1%
32 1
 
< 0.1%
30 1
 
< 0.1%
28 3
 
< 0.1%
26 2
 
< 0.1%
23 2
 
< 0.1%
22 2
 
< 0.1%
21 3
 
< 0.1%
20 18
0.2%

교육수료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

모범음식점여부
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
비대상
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
비대상 10000
100.0%

Length

2024-05-04T02:46:04.770057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:05.069212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비대상 10000
100.0%

급수시설
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9174 
상수도전용
 
826

Length

Max length5
Median length4
Mean length4.0826
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> 9174
91.7%
상수도전용 826
 
8.3%

Length

2024-05-04T02:46:05.497587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:05.803984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9174
91.7%
상수도전용 826
 
8.3%

업소위치
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
지상
5517 
<NA>
2217 
지하
1923 
지상2층이상
 
320
지상+지하
 
17
Other values (2)
 
6

Length

Max length6
Median length2
Mean length2.5765
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
지상 5517
55.2%
<NA> 2217
22.2%
지하 1923
 
19.2%
지상2층이상 320
 
3.2%
지상+지하 17
 
0.2%
도선 5
 
0.1%
도상 1
 
< 0.1%

Length

2024-05-04T02:46:06.184477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:06.549520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지상 5517
55.2%
na 2217
22.2%
지하 1923
 
19.2%
지상2층이상 320
 
3.2%
지상+지하 17
 
0.2%
도선 5
 
< 0.1%
도상 1
 
< 0.1%

종업원남
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9993 
1
 
6
2
 
1

Length

Max length4
Median length4
Mean length3.9979
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> 9993
99.9%
1 6
 
0.1%
2 1
 
< 0.1%

Length

2024-05-04T02:46:06.924882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:07.275809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9993
99.9%
1 6
 
0.1%
2 1
 
< 0.1%

종업원여
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9995 
1
 
5

Length

Max length4
Median length4
Mean length3.9985
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> 9995
> 99.9%
1 5
 
0.1%

Length

2024-05-04T02:46:07.620824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:07.938163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9995
> 99.9%
1 5
 
< 0.1%

급식소종류
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9987 
기타
 
6
사회복지시설
 
4
병원
 
3

Length

Max length6
Median length4
Mean length3.999
Min length2

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> 9987
99.9%
기타 6
 
0.1%
사회복지시설 4
 
< 0.1%
병원 3
 
< 0.1%

Length

2024-05-04T02:46:08.301422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:08.661888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9987
99.9%
기타 6
 
0.1%
사회복지시설 4
 
< 0.1%
병원 3
 
< 0.1%

평균급식인원수
Real number (ℝ)

MISSING 

Distinct48
Distinct (%)57.1%
Missing9916
Missing (%)99.2%
Infinite0
Infinite (%)0.0%
Mean93.892857
Minimum0
Maximum639
Zeros12
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:09.005944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q141.75
median58.5
Q394.75
95-th percentile395.65
Maximum639
Range639
Interquartile range (IQR)53

Descriptive statistics

Standard deviation118.68669
Coefficient of variation (CV)1.2640652
Kurtosis7.4031929
Mean93.892857
Median Absolute Deviation (MAD)26.5
Skewness2.6808893
Sum7887
Variance14086.531
MonotonicityNot monotonic
2024-05-04T02:46:09.448286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 12
 
0.1%
58 5
 
0.1%
53 3
 
< 0.1%
47 3
 
< 0.1%
100 3
 
< 0.1%
71 3
 
< 0.1%
50 3
 
< 0.1%
70 3
 
< 0.1%
51 2
 
< 0.1%
65 2
 
< 0.1%
Other values (38) 45
 
0.4%
(Missing) 9916
99.2%
ValueCountFrequency (%)
0 12
0.1%
23 1
 
< 0.1%
28 2
 
< 0.1%
29 1
 
< 0.1%
31 1
 
< 0.1%
32 1
 
< 0.1%
39 1
 
< 0.1%
40 1
 
< 0.1%
41 1
 
< 0.1%
42 1
 
< 0.1%
ValueCountFrequency (%)
639 1
< 0.1%
500 1
< 0.1%
450 1
< 0.1%
400 2
< 0.1%
371 1
< 0.1%
333 1
< 0.1%
263 1
< 0.1%
245 1
< 0.1%
227 1
< 0.1%
119 1
< 0.1%

최대급식인원수
Real number (ℝ)

MISSING 

Distinct34
Distinct (%)40.5%
Missing9916
Missing (%)99.2%
Infinite0
Infinite (%)0.0%
Mean56.190476
Minimum0
Maximum800
Zeros45
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:09.861221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q370.25
95-th percentile290.5
Maximum800
Range800
Interquartile range (IQR)70.25

Descriptive statistics

Standard deviation120.59985
Coefficient of variation (CV)2.1462686
Kurtosis18.827463
Mean56.190476
Median Absolute Deviation (MAD)0
Skewness3.9202343
Sum4720
Variance14544.325
MonotonicityNot monotonic
2024-05-04T02:46:10.382309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 45
 
0.4%
40 2
 
< 0.1%
97 2
 
< 0.1%
400 2
 
< 0.1%
142 2
 
< 0.1%
70 2
 
< 0.1%
10 2
 
< 0.1%
82 1
 
< 0.1%
58 1
 
< 0.1%
85 1
 
< 0.1%
Other values (24) 24
 
0.2%
(Missing) 9916
99.2%
ValueCountFrequency (%)
0 45
0.4%
3 1
 
< 0.1%
4 1
 
< 0.1%
7 1
 
< 0.1%
10 2
 
< 0.1%
20 1
 
< 0.1%
25 1
 
< 0.1%
40 2
 
< 0.1%
41 1
 
< 0.1%
52 1
 
< 0.1%
ValueCountFrequency (%)
800 1
< 0.1%
428 1
< 0.1%
400 2
< 0.1%
310 1
< 0.1%
180 1
< 0.1%
174 1
< 0.1%
142 2
< 0.1%
100 1
< 0.1%
98 1
< 0.1%
97 2
< 0.1%

1일급식인원수
Real number (ℝ)

MISSING 

Distinct51
Distinct (%)61.4%
Missing9917
Missing (%)99.2%
Infinite0
Infinite (%)0.0%
Mean165.33735
Minimum0
Maximum1484
Zeros12
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:10.814002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q155
median71
Q3140
95-th percentile779
Maximum1484
Range1484
Interquartile range (IQR)85

Descriptive statistics

Standard deviation254.1715
Coefficient of variation (CV)1.5372903
Kurtosis10.301081
Mean165.33735
Median Absolute Deviation (MAD)26
Skewness3.0296419
Sum13723
Variance64603.153
MonotonicityNot monotonic
2024-05-04T02:46:11.268474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12
 
0.1%
55 3
 
< 0.1%
53 3
 
< 0.1%
71 3
 
< 0.1%
50 3
 
< 0.1%
70 3
 
< 0.1%
51 2
 
< 0.1%
65 2
 
< 0.1%
58 2
 
< 0.1%
140 2
 
< 0.1%
Other values (41) 48
 
0.5%
(Missing) 9917
99.2%
ValueCountFrequency (%)
0 12
0.1%
50 3
 
< 0.1%
51 2
 
< 0.1%
53 3
 
< 0.1%
55 3
 
< 0.1%
56 1
 
< 0.1%
57 2
 
< 0.1%
58 2
 
< 0.1%
59 2
 
< 0.1%
60 2
 
< 0.1%
ValueCountFrequency (%)
1484 1
< 0.1%
1000 1
< 0.1%
900 1
< 0.1%
800 1
< 0.1%
790 1
< 0.1%
680 1
< 0.1%
639 1
< 0.1%
500 1
< 0.1%
400 1
< 0.1%
358 1
< 0.1%

일인당평균급식비
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)28.6%
Missing9916
Missing (%)99.2%
Infinite0
Infinite (%)0.0%
Mean3218.3571
Minimum0
Maximum50000
Zeros17
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:11.688407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12200
median2500
Q33500
95-th percentile5425
Maximum50000
Range50000
Interquartile range (IQR)1300

Descriptive statistics

Standard deviation5486.6264
Coefficient of variation (CV)1.704791
Kurtosis65.39985
Mean3218.3571
Median Absolute Deviation (MAD)511
Skewness7.6403238
Sum270342
Variance30103070
MonotonicityNot monotonic
2024-05-04T02:46:12.090171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 17
 
0.2%
2500 16
 
0.2%
3000 6
 
0.1%
5000 6
 
0.1%
2200 4
 
< 0.1%
2400 4
 
< 0.1%
4500 4
 
< 0.1%
3500 4
 
< 0.1%
4000 3
 
< 0.1%
2700 3
 
< 0.1%
Other values (14) 17
 
0.2%
(Missing) 9916
99.2%
ValueCountFrequency (%)
0 17
0.2%
2000 3
 
< 0.1%
2200 4
 
< 0.1%
2300 2
 
< 0.1%
2400 4
 
< 0.1%
2450 1
 
< 0.1%
2500 16
0.2%
2600 1
 
< 0.1%
2700 3
 
< 0.1%
2800 1
 
< 0.1%
ValueCountFrequency (%)
50000 1
 
< 0.1%
9000 1
 
< 0.1%
8000 1
 
< 0.1%
7700 1
 
< 0.1%
5500 1
 
< 0.1%
5000 6
0.1%
4500 4
< 0.1%
4200 1
 
< 0.1%
4000 3
< 0.1%
3500 4
< 0.1%

운영형태
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9944 
직영
 
49
(조합)위탁
 
7

Length

Max length6
Median length4
Mean length3.9916
Min length2

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> 9944
99.4%
직영 49
 
0.5%
(조합)위탁 7
 
0.1%

Length

2024-05-04T02:46:12.547528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:12.902424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9944
99.4%
직영 49
 
0.5%
조합)위탁 7
 
0.1%

영업장조리장면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct926
Distinct (%)38.3%
Missing7581
Missing (%)75.8%
Infinite0
Infinite (%)0.0%
Mean31.494163
Minimum0
Maximum1570.3
Zeros222
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:13.287591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.92
median17.07
Q332.83
95-th percentile100
Maximum1570.3
Range1570.3
Interquartile range (IQR)22.91

Descriptive statistics

Standard deviation66.488944
Coefficient of variation (CV)2.1111513
Kurtosis262.92524
Mean31.494163
Median Absolute Deviation (MAD)10.83
Skewness13.192707
Sum76184.38
Variance4420.7797
MonotonicityNot monotonic
2024-05-04T02:46:13.827734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 222
 
2.2%
10.0 150
 
1.5%
3.3 93
 
0.9%
20.0 85
 
0.9%
15.0 71
 
0.7%
30.0 60
 
0.6%
33.0 44
 
0.4%
13.0 39
 
0.4%
6.6 32
 
0.3%
12.0 27
 
0.3%
Other values (916) 1596
 
16.0%
(Missing) 7581
75.8%
ValueCountFrequency (%)
0.0 222
2.2%
1.0 5
 
0.1%
1.3 4
 
< 0.1%
1.32 1
 
< 0.1%
1.5 1
 
< 0.1%
1.6 1
 
< 0.1%
1.65 1
 
< 0.1%
2.0 2
 
< 0.1%
2.4 1
 
< 0.1%
2.45 1
 
< 0.1%
ValueCountFrequency (%)
1570.3 2
< 0.1%
990.8 1
< 0.1%
648.0 1
< 0.1%
546.0 1
< 0.1%
518.18 1
< 0.1%
462.0 1
< 0.1%
425.09 1
< 0.1%
406.7 1
< 0.1%
392.0 1
< 0.1%
355.05 1
< 0.1%

영업장객실면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct166
Distinct (%)26.3%
Missing9370
Missing (%)93.7%
Infinite0
Infinite (%)0.0%
Mean17.235889
Minimum0
Maximum855.93
Zeros430
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:14.315414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q318.335
95-th percentile66.3245
Maximum855.93
Range855.93
Interquartile range (IQR)18.335

Descriptive statistics

Standard deviation56.706703
Coefficient of variation (CV)3.2900365
Kurtosis123.20114
Mean17.235889
Median Absolute Deviation (MAD)0
Skewness9.6247767
Sum10858.61
Variance3215.6502
MonotonicityNot monotonic
2024-05-04T02:46:14.744453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 430
 
4.3%
20.0 5
 
0.1%
13.0 3
 
< 0.1%
29.0 3
 
< 0.1%
19.5 3
 
< 0.1%
33.0 3
 
< 0.1%
3.3 3
 
< 0.1%
36.0 3
 
< 0.1%
10.0 3
 
< 0.1%
30.0 3
 
< 0.1%
Other values (156) 171
 
1.7%
(Missing) 9370
93.7%
ValueCountFrequency (%)
0.0 430
4.3%
2.5 1
 
< 0.1%
3.3 3
 
< 0.1%
3.6 1
 
< 0.1%
5.0 1
 
< 0.1%
6.0 2
 
< 0.1%
6.6 1
 
< 0.1%
6.61 1
 
< 0.1%
6.73 1
 
< 0.1%
7.0 1
 
< 0.1%
ValueCountFrequency (%)
855.93 1
< 0.1%
753.4 1
< 0.1%
315.0 1
< 0.1%
282.59 1
< 0.1%
260.0 1
< 0.1%
228.18 1
< 0.1%
208.0 1
< 0.1%
185.34 1
< 0.1%
181.91 1
< 0.1%
179.93 1
< 0.1%

영업장무도장면적(㎡)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9568 
0
 
432

Length

Max length4
Median length4
Mean length3.8704
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> 9568
95.7%
0 432
 
4.3%

Length

2024-05-04T02:46:15.200034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:15.651805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9568
95.7%
0 432
 
4.3%

영업장기타면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct1524
Distinct (%)44.1%
Missing6548
Missing (%)65.5%
Infinite0
Infinite (%)0.0%
Mean46.698016
Minimum0
Maximum2126.34
Zeros510
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:16.007700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.3
median22.695
Q349.99
95-th percentile171.0145
Maximum2126.34
Range2126.34
Interquartile range (IQR)46.69

Descriptive statistics

Standard deviation96.325546
Coefficient of variation (CV)2.0627332
Kurtosis140.81688
Mean46.698016
Median Absolute Deviation (MAD)19.395
Skewness9.0861643
Sum161201.55
Variance9278.6108
MonotonicityNot monotonic
2024-05-04T02:46:16.407724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 510
 
5.1%
3.3 229
 
2.3%
6.6 67
 
0.7%
10.0 63
 
0.6%
33.0 51
 
0.5%
20.0 44
 
0.4%
30.0 42
 
0.4%
40.0 28
 
0.3%
16.5 28
 
0.3%
15.0 27
 
0.3%
Other values (1514) 2363
 
23.6%
(Missing) 6548
65.5%
ValueCountFrequency (%)
0.0 510
5.1%
0.33 1
 
< 0.1%
0.53 1
 
< 0.1%
0.54 1
 
< 0.1%
0.8 3
 
< 0.1%
0.91 1
 
< 0.1%
1.0 9
 
0.1%
1.02 1
 
< 0.1%
1.14 1
 
< 0.1%
1.15 1
 
< 0.1%
ValueCountFrequency (%)
2126.34 1
< 0.1%
2007.45 1
< 0.1%
1254.0 2
< 0.1%
1054.19 1
< 0.1%
983.0 1
< 0.1%
811.0 1
< 0.1%
767.6 1
< 0.1%
729.7 1
< 0.1%
684.11 1
< 0.1%
680.38 1
< 0.1%

업소내화장실면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct88
Distinct (%)8.8%
Missing9005
Missing (%)90.0%
Infinite0
Infinite (%)0.0%
Mean1.3504623
Minimum0
Maximum124.46
Zeros811
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:16.885927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6.603
Maximum124.46
Range124.46
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.7757505
Coefficient of variation (CV)4.276869
Kurtosis274.22187
Mean1.3504623
Median Absolute Deviation (MAD)0
Skewness14.474077
Sum1343.71
Variance33.359293
MonotonicityNot monotonic
2024-05-04T02:46:17.380218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 811
 
8.1%
5.0 23
 
0.2%
3.3 16
 
0.2%
3.0 14
 
0.1%
6.6 11
 
0.1%
10.0 10
 
0.1%
6.0 9
 
0.1%
4.0 6
 
0.1%
7.0 3
 
< 0.1%
9.0 3
 
< 0.1%
Other values (78) 89
 
0.9%
(Missing) 9005
90.0%
ValueCountFrequency (%)
0.0 811
8.1%
0.74 1
 
< 0.1%
0.83 1
 
< 0.1%
0.88 1
 
< 0.1%
1.0 1
 
< 0.1%
1.3 2
 
< 0.1%
1.32 1
 
< 0.1%
1.47 1
 
< 0.1%
1.56 1
 
< 0.1%
1.57 1
 
< 0.1%
ValueCountFrequency (%)
124.46 1
< 0.1%
93.8 1
< 0.1%
30.0 1
< 0.1%
23.5 1
< 0.1%
21.89 1
< 0.1%
21.02 1
< 0.1%
20.0 2
< 0.1%
19.57 1
< 0.1%
18.5 1
< 0.1%
17.38 1
< 0.1%

타업소공동화장실면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct30
Distinct (%)3.2%
Missing9071
Missing (%)90.7%
Infinite0
Infinite (%)0.0%
Mean0.7670183
Minimum0
Maximum40
Zeros827
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:17.786005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum40
Range40
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.2785067
Coefficient of variation (CV)4.2743527
Kurtosis71.971352
Mean0.7670183
Median Absolute Deviation (MAD)0
Skewness7.570741
Sum712.56
Variance10.748607
MonotonicityNot monotonic
2024-05-04T02:46:18.221808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.0 827
 
8.3%
3.3 39
 
0.4%
6.6 10
 
0.1%
5.0 9
 
0.1%
10.0 7
 
0.1%
3.0 5
 
0.1%
1.5 4
 
< 0.1%
16.0 2
 
< 0.1%
9.9 2
 
< 0.1%
2.0 2
 
< 0.1%
Other values (20) 22
 
0.2%
(Missing) 9071
90.7%
ValueCountFrequency (%)
0.0 827
8.3%
1.5 4
 
< 0.1%
1.6 1
 
< 0.1%
2.0 2
 
< 0.1%
2.2 1
 
< 0.1%
3.0 5
 
0.1%
3.3 39
 
0.4%
4.0 1
 
< 0.1%
4.6 1
 
< 0.1%
5.0 9
 
0.1%
ValueCountFrequency (%)
40.0 2
< 0.1%
33.0 1
< 0.1%
31.98 1
< 0.1%
30.0 1
< 0.1%
20.0 1
< 0.1%
16.5 1
< 0.1%
16.0 2
< 0.1%
15.0 1
< 0.1%
12.4 1
< 0.1%
12.0 1
< 0.1%

영업장탈의실면적(㎡)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9569 
0
 
431

Length

Max length4
Median length4
Mean length3.8707
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> 9569
95.7%
0 431
 
4.3%

Length

2024-05-04T02:46:19.143586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:19.489561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9569
95.7%
0 431
 
4.3%

영업장객석면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct613
Distinct (%)43.1%
Missing8578
Missing (%)85.8%
Infinite0
Infinite (%)0.0%
Mean39.299325
Minimum0
Maximum1550.35
Zeros311
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:19.851810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median20
Q342.06
95-th percentile123.095
Maximum1550.35
Range1550.35
Interquartile range (IQR)38.06

Descriptive statistics

Standard deviation86.384464
Coefficient of variation (CV)2.1981157
Kurtosis97.452245
Mean39.299325
Median Absolute Deviation (MAD)20
Skewness8.1962921
Sum55883.64
Variance7462.2757
MonotonicityNot monotonic
2024-05-04T02:46:20.349719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 311
 
3.1%
20.0 65
 
0.7%
30.0 49
 
0.5%
10.0 46
 
0.5%
40.0 32
 
0.3%
15.0 23
 
0.2%
50.0 23
 
0.2%
60.0 12
 
0.1%
6.0 12
 
0.1%
13.0 11
 
0.1%
Other values (603) 838
 
8.4%
(Missing) 8578
85.8%
ValueCountFrequency (%)
0.0 311
3.1%
1.0 2
 
< 0.1%
2.0 5
 
0.1%
2.16 1
 
< 0.1%
2.3 3
 
< 0.1%
2.4 1
 
< 0.1%
2.86 1
 
< 0.1%
3.0 11
 
0.1%
3.1 1
 
< 0.1%
3.11 2
 
< 0.1%
ValueCountFrequency (%)
1550.35 1
< 0.1%
900.0 1
< 0.1%
860.0 1
< 0.1%
856.0 1
< 0.1%
746.0 1
< 0.1%
730.16 1
< 0.1%
664.5 1
< 0.1%
600.0 1
< 0.1%
591.79 1
< 0.1%
569.81 1
< 0.1%

작업장면적(㎡)
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct417
Distinct (%)31.4%
Missing8672
Missing (%)86.7%
Infinite0
Infinite (%)0.0%
Mean168.29876
Minimum0
Maximum160325
Zeros270
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:20.883056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.3
median7.965
Q327.02
95-th percentile208.805
Maximum160325
Range160325
Interquartile range (IQR)23.72

Descriptive statistics

Standard deviation4401.1677
Coefficient of variation (CV)26.150922
Kurtosis1324.3924
Mean168.29876
Median Absolute Deviation (MAD)7.965
Skewness36.367822
Sum223500.75
Variance19370277
MonotonicityNot monotonic
2024-05-04T02:46:21.366468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 270
 
2.7%
3.3 178
 
1.8%
6.6 70
 
0.7%
10.0 40
 
0.4%
3.0 31
 
0.3%
20.0 29
 
0.3%
232.58 26
 
0.3%
1126.58 24
 
0.2%
6.0 18
 
0.2%
15.0 17
 
0.2%
Other values (407) 625
 
6.2%
(Missing) 8672
86.7%
ValueCountFrequency (%)
0.0 270
2.7%
1.0 16
 
0.2%
1.1 2
 
< 0.1%
1.65 1
 
< 0.1%
2.0 3
 
< 0.1%
2.2 1
 
< 0.1%
2.25 2
 
< 0.1%
2.5 1
 
< 0.1%
3.0 31
 
0.3%
3.14 1
 
< 0.1%
ValueCountFrequency (%)
160325.0 1
 
< 0.1%
1570.41 1
 
< 0.1%
1126.58 24
0.2%
819.03 1
 
< 0.1%
537.9 1
 
< 0.1%
426.0 1
 
< 0.1%
353.5 1
 
< 0.1%
352.43 1
 
< 0.1%
315.24 1
 
< 0.1%
267.74 1
 
< 0.1%

검사실면적(㎡)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9677 
0
 
323

Length

Max length4
Median length4
Mean length3.9031
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> 9677
96.8%
0 323
 
3.2%

Length

2024-05-04T02:46:21.836839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:22.309829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9677
96.8%
0 323
 
3.2%

진열(판매)대면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct68
Distinct (%)15.2%
Missing9552
Missing (%)95.5%
Infinite0
Infinite (%)0.0%
Mean9.9392634
Minimum0
Maximum1637
Zeros314
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:22.815150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32.025
95-th percentile18.5105
Maximum1637
Range1637
Interquartile range (IQR)2.025

Descriptive statistics

Standard deviation90.601927
Coefficient of variation (CV)9.1155575
Kurtosis253.59403
Mean9.9392634
Median Absolute Deviation (MAD)0
Skewness15.273464
Sum4452.79
Variance8208.7092
MonotonicityNot monotonic
2024-05-04T02:46:23.519834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 314
 
3.1%
3.3 25
 
0.2%
3.0 19
 
0.2%
1.0 9
 
0.1%
2.0 5
 
0.1%
6.6 5
 
0.1%
30.0 3
 
< 0.1%
10.0 3
 
< 0.1%
16.0 2
 
< 0.1%
5.0 2
 
< 0.1%
Other values (58) 61
 
0.6%
(Missing) 9552
95.5%
ValueCountFrequency (%)
0.0 314
3.1%
0.18 1
 
< 0.1%
0.32 1
 
< 0.1%
0.54 1
 
< 0.1%
0.72 1
 
< 0.1%
1.0 9
 
0.1%
1.1 1
 
< 0.1%
1.17 1
 
< 0.1%
1.42 1
 
< 0.1%
1.65 1
 
< 0.1%
ValueCountFrequency (%)
1637.0 1
< 0.1%
885.0 1
< 0.1%
430.0 1
< 0.1%
142.14 1
< 0.1%
84.2 1
< 0.1%
69.49 1
< 0.1%
66.4 1
< 0.1%
64.0 1
< 0.1%
59.6 1
< 0.1%
56.0 1
< 0.1%

창고(보관소)면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct44
Distinct (%)9.9%
Missing9555
Missing (%)95.5%
Infinite0
Infinite (%)0.0%
Mean2.9437303
Minimum0
Maximum206
Zeros391
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:24.358007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20
Maximum206
Range206
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.987038
Coefficient of variation (CV)4.7514673
Kurtosis108.65557
Mean2.9437303
Median Absolute Deviation (MAD)0
Skewness8.9651607
Sum1309.96
Variance195.63724
MonotonicityNot monotonic
2024-05-04T02:46:25.097059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0.0 391
 
3.9%
33.0 3
 
< 0.1%
3.0 3
 
< 0.1%
2.0 2
 
< 0.1%
10.0 2
 
< 0.1%
25.0 2
 
< 0.1%
59.08 2
 
< 0.1%
20.0 2
 
< 0.1%
3.3 2
 
< 0.1%
5.0 2
 
< 0.1%
Other values (34) 34
 
0.3%
(Missing) 9555
95.5%
ValueCountFrequency (%)
0.0 391
3.9%
1.0 1
 
< 0.1%
1.4 1
 
< 0.1%
1.6 1
 
< 0.1%
1.8 1
 
< 0.1%
2.0 2
 
< 0.1%
2.24 1
 
< 0.1%
2.6 1
 
< 0.1%
2.87 1
 
< 0.1%
3.0 3
 
< 0.1%
ValueCountFrequency (%)
206.0 1
< 0.1%
97.5 1
< 0.1%
78.5 1
< 0.1%
66.0 1
< 0.1%
61.75 1
< 0.1%
59.08 2
< 0.1%
40.0 1
< 0.1%
39.6 1
< 0.1%
37.2 1
< 0.1%
35.56 1
< 0.1%
Distinct7179
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T02:46:26.127237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6875 ?
Unique (%)68.8%

Sample

1st row3030000-101-2021-****6
2nd row3200000-107-2021-00068
3rd row3230000-105-2021-00009
4th row3130000-134-2021-00064
5th row3110000-134-2021-00099
ValueCountFrequency (%)
3220000-101-2021-****5 37
 
0.4%
3220000-101-2021-****2 35
 
0.4%
3220000-101-2021-****8 33
 
0.3%
3220000-101-2021-****6 32
 
0.3%
3220000-101-2021-****1 32
 
0.3%
3220000-101-2021-****4 31
 
0.3%
3220000-101-2021-****9 30
 
0.3%
3220000-101-2021-****0 29
 
0.3%
3220000-101-2021-****7 28
 
0.3%
3220000-101-2021-****3 28
 
0.3%
Other values (7169) 9685
96.9%
2024-05-04T02:46:27.689359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 82866
37.7%
1 31981
 
14.5%
- 30000
 
13.6%
2 27468
 
12.5%
3 15990
 
7.3%
* 12068
 
5.5%
4 6185
 
2.8%
7 4551
 
2.1%
5 2724
 
1.2%
8 2248
 
1.0%
Other values (2) 3919
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 177932
80.9%
Dash Punctuation 30000
 
13.6%
Other Punctuation 12068
 
5.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 82866
46.6%
1 31981
 
18.0%
2 27468
 
15.4%
3 15990
 
9.0%
4 6185
 
3.5%
7 4551
 
2.6%
5 2724
 
1.5%
8 2248
 
1.3%
6 2161
 
1.2%
9 1758
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%
Other Punctuation
ValueCountFrequency (%)
* 12068
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 82866
37.7%
1 31981
 
14.5%
- 30000
 
13.6%
2 27468
 
12.5%
3 15990
 
7.3%
* 12068
 
5.5%
4 6185
 
2.8%
7 4551
 
2.1%
5 2724
 
1.2%
8 2248
 
1.0%
Other values (2) 3919
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 82866
37.7%
1 31981
 
14.5%
- 30000
 
13.6%
2 27468
 
12.5%
3 15990
 
7.3%
* 12068
 
5.5%
4 6185
 
2.8%
7 4551
 
2.1%
5 2724
 
1.2%
8 2248
 
1.0%
Other values (2) 3919
 
1.8%

조건부허가시작일
Real number (ℝ)

MISSING  SKEWED 

Distinct113
Distinct (%)6.2%
Missing8182
Missing (%)81.8%
Infinite0
Infinite (%)0.0%
Mean20210296
Minimum20210104
Maximum20230215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:28.224911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210104
5-th percentile20210111
Q120210204
median20210304
Q320210326
95-th percentile20210415
Maximum20230215
Range20111
Interquartile range (IQR)122

Descriptive statistics

Standard deviation709.95752
Coefficient of variation (CV)3.5128507 × 10-5
Kurtosis698.96289
Mean20210296
Median Absolute Deviation (MAD)94
Skewness25.817486
Sum3.6742318 × 1010
Variance504039.69
MonotonicityNot monotonic
2024-05-04T02:46:28.923142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210401 97
 
1.0%
20210318 68
 
0.7%
20210304 64
 
0.6%
20210415 58
 
0.6%
20210215 47
 
0.5%
20210121 42
 
0.4%
20210218 41
 
0.4%
20210219 41
 
0.4%
20210315 41
 
0.4%
20210226 40
 
0.4%
Other values (103) 1279
 
12.8%
(Missing) 8182
81.8%
ValueCountFrequency (%)
20210104 10
 
0.1%
20210105 4
 
< 0.1%
20210106 7
 
0.1%
20210107 17
0.2%
20210108 35
0.4%
20210109 2
 
< 0.1%
20210110 2
 
< 0.1%
20210111 38
0.4%
20210112 4
 
< 0.1%
20210113 14
 
0.1%
ValueCountFrequency (%)
20230215 1
< 0.1%
20230125 1
< 0.1%
20220524 1
< 0.1%
20210829 1
< 0.1%
20210507 1
< 0.1%
20210430 1
< 0.1%
20210429 1
< 0.1%
20210428 1
< 0.1%
20210426 2
< 0.1%
20210425 2
< 0.1%

조건부허가종료일
Real number (ℝ)

MISSING 

Distinct143
Distinct (%)7.9%
Missing8182
Missing (%)81.8%
Infinite0
Infinite (%)0.0%
Mean20210747
Minimum20210105
Maximum20320906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T02:46:29.582287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210105
5-th percentile20210120
Q120210218
median20210317
Q320210410
95-th percentile20210502
Maximum20320906
Range110801
Interquartile range (IQR)192

Descriptive statistics

Standard deviation4496.0558
Coefficient of variation (CV)0.00022245866
Kurtosis316.45127
Mean20210747
Median Absolute Deviation (MAD)96
Skewness15.954803
Sum3.6743139 × 1010
Variance20214518
MonotonicityNot monotonic
2024-05-04T02:46:30.081401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210331 97
 
1.0%
20210414 61
 
0.6%
20210317 59
 
0.6%
20210325 45
 
0.4%
20210303 41
 
0.4%
20210217 41
 
0.4%
20210428 40
 
0.4%
20210225 39
 
0.4%
20210211 38
 
0.4%
20210304 38
 
0.4%
Other values (133) 1319
 
13.2%
(Missing) 8182
81.8%
ValueCountFrequency (%)
20210105 1
 
< 0.1%
20210107 2
 
< 0.1%
20210108 1
 
< 0.1%
20210109 3
 
< 0.1%
20210110 2
 
< 0.1%
20210111 1
 
< 0.1%
20210112 3
 
< 0.1%
20210113 3
 
< 0.1%
20210114 23
0.2%
20210115 1
 
< 0.1%
ValueCountFrequency (%)
20320906 1
 
< 0.1%
20291218 1
 
< 0.1%
20290410 1
 
< 0.1%
20250930 1
 
< 0.1%
20240827 1
 
< 0.1%
20231104 1
 
< 0.1%
20230814 1
 
< 0.1%
20230731 2
 
< 0.1%
20230730 17
0.2%
20230324 1
 
< 0.1%

내외국인구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
내국인
9874 
외국인
 
126

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
내국인 9874
98.7%
외국인 126
 
1.3%

Length

2024-05-04T02:46:30.584063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:46:31.005455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
내국인 9874
98.7%
외국인 126
 
1.3%

국적
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대한민국
9874 
<NA>
 
74
미국
 
30
캐나다
 
9
영국
 
3
Other values (7)
 
10

Length

Max length6
Median length4
Mean length3.9916
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
대한민국 9874
98.7%
<NA> 74
 
0.7%
미국 30
 
0.3%
캐나다 9
 
0.1%
영국 3
 
< 0.1%
몽골 2
 
< 0.1%
중국 2
 
< 0.1%
뉴질랜드 2
 
< 0.1%
우즈베키스탄 1
 
< 0.1%
싱가포르 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2024-05-04T02:46:31.453409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대한민국 9874
98.7%
na 74
 
0.7%
미국 30
 
0.3%
캐나다 9
 
0.1%
영국 3
 
< 0.1%
몽골 2
 
< 0.1%
중국 2
 
< 0.1%
뉴질랜드 2
 
< 0.1%
우즈베키스탄 1
 
< 0.1%
싱가포르 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Sample

시군구코드업종코드년도업소일련번호업종명허가신고일업소명소재지도로명소재지지번영업장면적(㎡)영업자시작일법인명법인번호소재지시작일행정동명폐업일자폐업구분폐업사유업태명지상_부터지상_까지지하_부터지하_까지총층수교육수료일자모범음식점여부급수시설업소위치종업원남종업원여급식소종류평균급식인원수최대급식인원수1일급식인원수일인당평균급식비운영형태영업장조리장면적(㎡)영업장객실면적(㎡)영업장무도장면적(㎡)영업장기타면적(㎡)업소내화장실면적(㎡)타업소공동화장실면적(㎡)영업장탈의실면적(㎡)영업장객석면적(㎡)작업장면적(㎡)검사실면적(㎡)진열(판매)대면적(㎡)창고(보관소)면적(㎡)허가(신고)번호조건부허가시작일조건부허가종료일내외국인구분국적
912930300001012021126일반음식점20210315신월서울특별시 성동구 연무장길 5-9, 1,2층 (성수동2가)서울특별시 성동구 성수동2가 301번지 61호<NA>20210315<NA><NA>20210315성수2가제1동<NA><NA><NA>일식<NA><NA><NA><NA><NA><NA>비대상<NA>지상<NA><NA><NA><NA><NA><NA><NA><NA>110.42<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3030000-101-2021-****6<NA><NA>내국인대한민국
83143200000107202168즉석판매제조가공업20210309핸드맘서울특별시 관악구 청림3길 10, 지하1층 (봉천동, 서희스타힐즈)서울특별시 관악구 봉천동 1729번지 서희스타힐즈<NA>20210309<NA><NA>20210309청림동<NA><NA><NA>즉석판매제조가공업<NA><NA><NA><NA><NA><NA>비대상<NA>지상<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>23.0<NA><NA><NA>3200000-107-2021-00068<NA><NA>내국인대한민국
13062323000010520219집단급식소20210412은빛 어린이집서울특별시 송파구 삼전로4길 4, (삼전동)서울특별시 송파구 삼전동 35번지150.020210412<NA><NA>20210412삼전동<NA><NA><NA>어린이집13000<NA>비대상<NA>지상<NA><NA><NA>850852000<NA>150.0<NA><NA>0.00.00.0<NA><NA>0.0<NA><NA>0.03230000-105-2021-00009<NA><NA>내국인대한민국
57053130000134202164건강기능식품일반판매업20210217다경잡화점서울특별시 마포구 숭문길 106, 101동 1109호 (염리동, 상록아파트)서울특별시 마포구 염리동 515번지 1호 101 상록아파트-1109<NA>20210217<NA><NA>20210217염리동<NA><NA><NA>전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA>비대상<NA>지상<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3130000-134-2021-00064<NA><NA>내국인대한민국
133403110000134202199건강기능식품일반판매업20210414박유림상사서울특별시 은평구 은평로10길 25-1, 1층 우측호 (응암동)서울특별시 은평구 응암동 100번지 45호<NA>20210414<NA><NA>20210414응암제1동<NA><NA><NA>전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA>비대상<NA>지상<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3110000-134-2021-00099<NA><NA>내국인대한민국
542932300001072021144즉석판매제조가공업20210216(주)수에프앤비서울특별시 송파구 충민로 66, 현대시티아울렛 가든파이브점 지하1층 (문정동)서울특별시 송파구 문정동 634번지 가든파이브라이프<NA>20210216(주)수에프앤비135811024508520210216문정1동20210225기타조건부기간 완료에 따른 폐업처리(자동폐업)즉석판매제조가공업<NA><NA><NA><NA><NA><NA>비대상<NA>지하<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3.3<NA><NA><NA>3230000-107-2021-001442021021920210225내국인대한민국
51783150000101202191일반음식점20210215맘스터치 우장산역점서울특별시 강서구 강서로 271, 2층 2호 (내발산동)서울특별시 강서구 내발산동 719번지 5호 2층 2호<NA>20210215<NA><NA>20210215발산제1동<NA><NA><NA>기타22<NA><NA>3<NA>비대상상수도전용지상2층이상<NA><NA><NA><NA><NA><NA><NA><NA>60.0<NA><NA><NA><NA><NA><NA>115.75<NA><NA><NA><NA>3150000-101-2021-****1<NA><NA>내국인대한민국
526032200001012021148일반음식점20210215정성육(본)서울특별시 강남구 논현로 334, 1층 (역삼동)서울특별시 강남구 역삼동 776번지 22호<NA>20210215<NA><NA>20210215역삼1동<NA><NA><NA>한식11<NA><NA><NA><NA>비대상<NA>지상<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>23.0<NA><NA><NA><NA><NA><NA><NA><NA>3220000-101-2021-****8<NA><NA>내국인대한민국
783032300001072021185즉석판매제조가공업20210304이씨푸드서울특별시 송파구 충민로 66, NC백화점 송파점 (문정동)서울특별시 송파구 문정동 634번지 가든파이브라이프<NA>20210304<NA><NA>20210304문정1동20210316기타조건부기간 완료에 따른 폐업처리(자동폐업)즉석판매제조가공업<NA><NA><NA><NA><NA><NA>비대상<NA>지하<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3.3<NA><NA><NA>3230000-107-2021-001852021031020210316내국인대한민국
32053050000101202126일반음식점20210126육회??&딱새우서울특별시 동대문구 사가정로 221, 1층 106호 (장안동)서울특별시 동대문구 장안동 100번지 8호<NA>20210126<NA><NA>20210126장안제1동<NA><NA><NA>한식<NA><NA><NA><NA><NA><NA>비대상<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>26.64<NA><NA><NA><NA><NA><NA><NA><NA>3050000-101-2021-****6<NA><NA>내국인대한민국
시군구코드업종코드년도업소일련번호업종명허가신고일업소명소재지도로명소재지지번영업장면적(㎡)영업자시작일법인명법인번호소재지시작일행정동명폐업일자폐업구분폐업사유업태명지상_부터지상_까지지하_부터지하_까지총층수교육수료일자모범음식점여부급수시설업소위치종업원남종업원여급식소종류평균급식인원수최대급식인원수1일급식인원수일인당평균급식비운영형태영업장조리장면적(㎡)영업장객실면적(㎡)영업장무도장면적(㎡)영업장기타면적(㎡)업소내화장실면적(㎡)타업소공동화장실면적(㎡)영업장탈의실면적(㎡)영업장객석면적(㎡)작업장면적(㎡)검사실면적(㎡)진열(판매)대면적(㎡)창고(보관소)면적(㎡)허가(신고)번호조건부허가시작일조건부허가종료일내외국인구분국적
28233120000134202120건강기능식품일반판매업20210122잼잇업(JAMITUP)서울특별시 서대문구 연희로41길 69-9, 101호 (홍은동, 그랜드빌라)서울특별시 서대문구 홍은동 206번지 2호 그랜드빌라<NA>20210122<NA><NA>20210122홍은제2동20220124자진폐업영업부진전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA>비대상<NA>지상<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3120000-134-2021-00020<NA><NA>내국인대한민국
117363140000101202190일반음식점20210401양통꼬치서울특별시 양천구 오목로54길 2, 1층 (목동)서울특별시 양천구 목동 405번지 216호<NA>20210401<NA><NA>20210401목1동<NA><NA><NA>한식11<NA><NA><NA><NA>비대상<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>92.15<NA><NA><NA><NA><NA><NA><NA><NA>3140000-101-2021-****0<NA><NA>외국인<NA>
1299632300001072021313즉석판매제조가공업20210412하랑이랑서울특별시 송파구 백제고분로36길 26, 한석빌딩 1~4층 (석촌동)서울특별시 송파구 석촌동 60번지 8호 한석빌딩<NA>20210412<NA><NA>20210412석촌동20210903자진폐업<NA>즉석판매제조가공업<NA><NA><NA><NA><NA><NA>비대상<NA>지상2층이상<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1126.58<NA><NA><NA>3230000-107-2021-003132021041220210716내국인대한민국
30703100000101202128일반음식점20210125엄마손서울특별시 노원구 노원로 462, 선한목사교회 1층 좌측호 (상계동)서울특별시 노원구 상계동 370번지 14호 선한목사교회<NA>20210125<NA><NA>20210125상계2동<NA><NA><NA>분식<NA><NA><NA><NA><NA><NA>비대상<NA>지상<NA><NA><NA><NA><NA><NA><NA><NA>22.0<NA><NA><NA><NA><NA><NA>40.0<NA><NA><NA><NA>3100000-101-2021-****8<NA><NA>내국인대한민국
45403060000104202117휴게음식점20210205GS25 중랑우림점서울특별시 중랑구 봉우재로65길 32, 1층 (망우동)서울특별시 중랑구 망우동 462번지 46호<NA>20210205<NA><NA>20210205망우본동<NA><NA><NA>편의점11<NA><NA><NA><NA>비대상<NA>지상<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6.6<NA><NA><NA><NA><NA><NA><NA><NA>3060000-104-2021-00017<NA><NA>내국인대한민국
512432200001072021107즉석판매제조가공업20210210감동푸드(한시적)서울특별시 강남구 도곡로 401, 롯데백화점 강남점 지하1층 (대치동)서울특별시 강남구 대치동 937번지 롯데백화점<NA>20210210<NA><NA>20210210대치1동20210225기타조건부기간 완료에 따른 폐업처리(자동폐업)즉석판매제조가공업<NA><NA><NA><NA><NA><NA>비대상<NA>지하<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3220000-107-2021-001072021021920210225내국인대한민국
108163040000104202150휴게음식점20210326우럼마왕만두서울특별시 광진구 군자로 84, 1층 (군자동)서울특별시 광진구 군자동 363번지 4호 1층<NA>20210326<NA><NA>20210326군자동20220706자진폐업<NA>일반조리판매11<NA><NA><NA><NA>비대상<NA>지상<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>18.0<NA><NA><NA><NA>3040000-104-2021-00050<NA><NA>내국인대한민국
636311000013420213건강기능식품일반판매업20210106프랜드팜서울특별시 은평구 연서로 270-1, 1층 좌측호 (불광동)서울특별시 은평구 불광동 316번지 1호<NA>20210106<NA><NA>20210106불광제1동<NA><NA><NA>전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA>비대상<NA>지상<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3110000-134-2021-00003<NA><NA>내국인대한민국
448313000010420213휴게음식점20210105씨유 상수팜팜점서울특별시 마포구 와우산로3길 21, 1층 (상수동)서울특별시 마포구 상수동 337번지 2호<NA>20210105<NA><NA>20210105서강동<NA><NA><NA>편의점<NA><NA><NA><NA><NA><NA>비대상<NA>지상<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3.3<NA><NA><NA><NA><NA><NA><NA><NA>3130000-104-2021-00003<NA><NA>내국인대한민국
121703030000104202138휴게음식점20210405아쿠아산타 성수카페서울특별시 성동구 연무장길 81, 1층 107호 (성수동2가)서울특별시 성동구 성수동2가 271번지 24호 남경빌딩<NA>20210405<NA><NA>20210405성수2가제1동<NA><NA><NA>커피숍<NA><NA><NA><NA><NA><NA>비대상<NA>지상<NA><NA><NA><NA><NA><NA><NA><NA>49.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3030000-104-2021-00038<NA><NA>내국인대한민국