Overview

Dataset statistics

Number of variables39
Number of observations539
Missing cells1317
Missing cells (%)6.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory169.1 KiB
Average record size in memory321.2 B

Variable types

Text10
DateTime2
Categorical25
Numeric2

Dataset

Description이 데이터는 서울특별시 동작구의 빨래방, 세탁소, 운동화빨래방 등 의류 기타섬유제품이나 피혁제품등을 세탁하는 업소 정보를 포함하고 있습니다. 좌표안내 : 중부원점 TM(EPSG:2097) 좌표계에 따른 해당위치의 좌표정보이며 위경도 좌표는 제공하고 있지 않습니다. 본 데이터는 3일전 자료를 제공합니다.
Author서울특별시 동작구
URLhttps://www.data.go.kr/data/15094597/fileData.do

Alerts

업태구분명 is highly imbalanced (67.5%)Imbalance
건물지상층수 is highly imbalanced (50.6%)Imbalance
건물지하층수 is highly imbalanced (53.2%)Imbalance
사용시작지하층 is highly imbalanced (56.1%)Imbalance
사용끝지하층 is highly imbalanced (59.5%)Imbalance
한실수 is highly imbalanced (50.4%)Imbalance
조건부허가신고사유 is highly imbalanced (74.0%)Imbalance
조건부허가시작일자 is highly imbalanced (86.3%)Imbalance
건물소유구분명 is highly imbalanced (73.8%)Imbalance
세탁기수 is highly imbalanced (60.3%)Imbalance
여성종사자수 is highly imbalanced (80.9%)Imbalance
남성종사자수 is highly imbalanced (88.1%)Imbalance
회수건조수 is highly imbalanced (68.1%)Imbalance
침대수 is highly imbalanced (69.8%)Imbalance
다중이용업소여부 is highly imbalanced (52.3%)Imbalance
폐업일자 has 152 (28.2%) missing valuesMissing
도로명주소 has 240 (44.5%) missing valuesMissing
도로명우편번호 has 255 (47.3%) missing valuesMissing
좌표정보(X) has 51 (9.5%) missing valuesMissing
좌표정보(Y) has 51 (9.5%) missing valuesMissing
위생업태명 has 26 (4.8%) missing valuesMissing
조건부허가종료일자 has 537 (99.6%) missing valuesMissing
관리번호 has unique valuesUnique
소재지면적 has 66 (12.2%) zerosZeros

Reproduction

Analysis started2023-12-11 23:19:07.965992
Analysis finished2023-12-11 23:19:09.281723
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct539
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-12T08:19:09.470715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters11858
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique539 ?
Unique (%)100.0%

Sample

1st row3190000-205-1987-01675
2nd row3190000-205-1987-01676
3rd row3190000-205-1987-01677
4th row3190000-205-1987-01678
5th row3190000-205-1987-01679
ValueCountFrequency (%)
3190000-205-1987-01675 1
 
0.2%
3190000-205-1999-01730 1
 
0.2%
3190000-205-2001-00007 1
 
0.2%
3190000-205-2001-00006 1
 
0.2%
3190000-205-2001-00005 1
 
0.2%
3190000-205-2001-00004 1
 
0.2%
3190000-205-2001-00003 1
 
0.2%
3190000-205-2001-00002 1
 
0.2%
3190000-205-2001-00001 1
 
0.2%
3190000-205-2000-00007 1
 
0.2%
Other values (529) 529
98.1%
2023-12-12T08:19:10.063943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4176
35.2%
- 1617
 
13.6%
1 1486
 
12.5%
9 1269
 
10.7%
2 871
 
7.3%
3 683
 
5.8%
5 675
 
5.7%
8 410
 
3.5%
7 298
 
2.5%
6 223
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10241
86.4%
Dash Punctuation 1617
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4176
40.8%
1 1486
 
14.5%
9 1269
 
12.4%
2 871
 
8.5%
3 683
 
6.7%
5 675
 
6.6%
8 410
 
4.0%
7 298
 
2.9%
6 223
 
2.2%
4 150
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 1617
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11858
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4176
35.2%
- 1617
 
13.6%
1 1486
 
12.5%
9 1269
 
10.7%
2 871
 
7.3%
3 683
 
5.8%
5 675
 
5.7%
8 410
 
3.5%
7 298
 
2.5%
6 223
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11858
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4176
35.2%
- 1617
 
13.6%
1 1486
 
12.5%
9 1269
 
10.7%
2 871
 
7.3%
3 683
 
5.8%
5 675
 
5.7%
8 410
 
3.5%
7 298
 
2.5%
6 223
 
1.9%

인허가일자
Date

Distinct395
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum1987-06-01 00:00:00
Maximum2020-10-22 00:00:00
2023-12-12T08:19:10.346994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:19:10.634746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
3
387 
1
152 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 387
71.8%
1 152
 
28.2%

Length

2023-12-12T08:19:10.925207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:11.110430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 387
71.8%
1 152
 
28.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
폐업
387 
영업/정상
152 

Length

Max length5
Median length2
Mean length2.8460111
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 387
71.8%
영업/정상 152
 
28.2%

Length

2023-12-12T08:19:11.335875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:11.536371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 387
71.8%
영업/정상 152
 
28.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2
387 
1
152 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 387
71.8%
1 152
 
28.2%

Length

2023-12-12T08:19:11.770330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:11.949405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 387
71.8%
1 152
 
28.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
폐업
387 
영업
152 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 387
71.8%
영업 152
 
28.2%

Length

2023-12-12T08:19:12.148479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:12.337373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 387
71.8%
영업 152
 
28.2%

폐업일자
Date

MISSING 

Distinct322
Distinct (%)83.2%
Missing152
Missing (%)28.2%
Memory size4.3 KiB
Minimum1994-12-30 00:00:00
Maximum2021-10-18 00:00:00
2023-12-12T08:19:12.998109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:19:13.280267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지면적
Real number (ℝ)

ZEROS 

Distinct372
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.638961
Minimum0
Maximum657.1
Zeros66
Zeros (%)12.2%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2023-12-12T08:19:13.596147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q118
median26.3
Q339.55
95-th percentile240.755
Maximum657.1
Range657.1
Interquartile range (IQR)21.55

Descriptive statistics

Standard deviation87.057346
Coefficient of variation (CV)1.6858849
Kurtosis15.143778
Mean51.638961
Median Absolute Deviation (MAD)9.7
Skewness3.7286872
Sum27833.4
Variance7578.9814
MonotonicityNot monotonic
2023-12-12T08:19:13.872864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 66
 
12.2%
33.0 10
 
1.9%
23.1 8
 
1.5%
26.4 7
 
1.3%
16.7 5
 
0.9%
23.5 5
 
0.9%
29.7 5
 
0.9%
26.5 4
 
0.7%
24.0 4
 
0.7%
66.0 4
 
0.7%
Other values (362) 421
78.1%
ValueCountFrequency (%)
0.0 66
12.2%
1.0 2
 
0.4%
3.3 3
 
0.6%
9.4 1
 
0.2%
9.9 1
 
0.2%
10.0 1
 
0.2%
10.6 1
 
0.2%
11.61 1
 
0.2%
12.06 1
 
0.2%
12.08 1
 
0.2%
ValueCountFrequency (%)
657.1 1
0.2%
505.44 1
0.2%
496.49 1
0.2%
494.95 1
0.2%
494.8 2
0.4%
493.92 1
0.2%
488.72 1
0.2%
443.37 1
0.2%
422.46 1
0.2%
405.2 1
0.2%

소재지우편번호
Real number (ℝ)

Distinct82
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean155814.93
Minimum28.16
Maximum156883
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2023-12-12T08:19:14.130332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28.16
5-th percentile156030
Q1156804
median156823
Q3156846
95-th percentile156863
Maximum156883
Range156854.84
Interquartile range (IQR)42

Descriptive statistics

Standard deviation11668.763
Coefficient of variation (CV)0.074888604
Kurtosis175.91983
Mean155814.93
Median Absolute Deviation (MAD)21
Skewness-13.306923
Sum83984247
Variance1.3616002 × 108
MonotonicityNot monotonic
2023-12-12T08:19:14.295959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
156030.0 28
 
5.2%
156090.0 24
 
4.5%
156846.0 15
 
2.8%
156827.0 13
 
2.4%
156060.0 13
 
2.4%
156815.0 13
 
2.4%
156825.0 13
 
2.4%
156855.0 13
 
2.4%
156811.0 12
 
2.2%
156821.0 12
 
2.2%
Other values (72) 383
71.1%
ValueCountFrequency (%)
28.16 1
 
0.2%
65.62 1
 
0.2%
127.0 1
 
0.2%
150841.0 1
 
0.2%
156010.0 7
 
1.3%
156020.0 3
 
0.6%
156030.0 28
5.2%
156031.0 7
 
1.3%
156060.0 13
2.4%
156070.0 3
 
0.6%
ValueCountFrequency (%)
156883.0 3
 
0.6%
156881.0 1
 
0.2%
156879.0 11
2.0%
156878.0 1
 
0.2%
156877.0 1
 
0.2%
156875.0 1
 
0.2%
156873.0 2
 
0.4%
156871.0 5
0.9%
156863.0 4
 
0.7%
156862.0 4
 
0.7%

지번주소
Text

Distinct490
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-12T08:19:14.771717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length40
Mean length24.762523
Min length6

Characters and Unicode

Total characters13347
Distinct characters145
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

Unique449 ?
Unique (%)83.3%

Sample

1st row서울특별시 동작구 사당동 141-156번지
2nd row서울특별시 동작구 사당동 708-457번지
3rd row서울특별시 동작구 사당동 1131-0번지 영아A 상가 203호
4th row서울특별시 동작구 상도1동 326-14번지
5th row서울특별시 동작구 흑석동 79-93번지
ValueCountFrequency (%)
서울특별시 536
22.2%
동작구 535
22.2%
사당동 165
 
6.8%
상도동 116
 
4.8%
신대방동 67
 
2.8%
흑석동 50
 
2.1%
노량진동 47
 
2.0%
대방동 41
 
1.7%
상도1동 26
 
1.1%
1층 20
 
0.8%
Other values (611) 807
33.5%
2023-12-12T08:19:15.262872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2332
17.5%
동 1130
 
8.5%
1 592
 
4.4%
작 544
 
4.1%
서 536
 
4.0%
특 536
 
4.0%
별 536
 
4.0%
시 536
 
4.0%
구 536
 
4.0%
울 536
 
4.0%
Other values (135) 5533
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7792
58.4%
Decimal Number 2714
 
20.3%
Space Separator 2332
 
17.5%
Dash Punctuation 452
 
3.4%
Close Punctuation 20
 
0.1%
Open Punctuation 20
 
0.1%
Uppercase Letter 12
 
0.1%
Other Punctuation 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1130
14.5%
작 544
 
7.0%
서 536
 
6.9%
특 536
 
6.9%
별 536
 
6.9%
시 536
 
6.9%
구 536
 
6.9%
울 536
 
6.9%
지 504
 
6.5%
번 487
 
6.2%
Other values (113) 1911
24.5%
Decimal Number
ValueCountFrequency (%)
1 592
21.8%
2 388
14.3%
3 313
11.5%
0 299
11.0%
4 240
8.8%
5 209
 
7.7%
6 202
 
7.4%
7 171
 
6.3%
9 156
 
5.7%
8 144
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
A 7
58.3%
B 3
25.0%
P 1
 
8.3%
T 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
? 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
2332
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 452
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7792
58.4%
Common 5541
41.5%
Latin 14
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1130
14.5%
작 544
 
7.0%
서 536
 
6.9%
특 536
 
6.9%
별 536
 
6.9%
시 536
 
6.9%
구 536
 
6.9%
울 536
 
6.9%
지 504
 
6.5%
번 487
 
6.2%
Other values (113) 1911
24.5%
Common
ValueCountFrequency (%)
2332
42.1%
1 592
 
10.7%
- 452
 
8.2%
2 388
 
7.0%
3 313
 
5.6%
0 299
 
5.4%
4 240
 
4.3%
5 209
 
3.8%
6 202
 
3.6%
7 171
 
3.1%
Other values (6) 343
 
6.2%
Latin
ValueCountFrequency (%)
A 7
50.0%
B 3
21.4%
a 1
 
7.1%
P 1
 
7.1%
T 1
 
7.1%
e 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7792
58.4%
ASCII 5555
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2332
42.0%
1 592
 
10.7%
- 452
 
8.1%
2 388
 
7.0%
3 313
 
5.6%
0 299
 
5.4%
4 240
 
4.3%
5 209
 
3.8%
6 202
 
3.6%
7 171
 
3.1%
Other values (12) 357
 
6.4%
Hangul
ValueCountFrequency (%)
동 1130
14.5%
작 544
 
7.0%
서 536
 
6.9%
특 536
 
6.9%
별 536
 
6.9%
시 536
 
6.9%
구 536
 
6.9%
울 536
 
6.9%
지 504
 
6.5%
번 487
 
6.2%
Other values (113) 1911
24.5%

도로명주소
Text

MISSING 

Distinct285
Distinct (%)95.3%
Missing240
Missing (%)44.5%
Memory size4.3 KiB
2023-12-12T08:19:15.587601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length23.575251
Min length3

Characters and Unicode

Total characters7049
Distinct characters77
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique274 ?
Unique (%)91.6%

Sample

1st row서울특별시 동작구 사당로27길 24 (사당동)
2nd row서울특별시 동작구 동작대로27다길 41 (사당동)
3rd row서울특별시 동작구 사당로16길 57 (사당동)
4th row서울특별시 동작구 사당로23길 126 (사당동)
5th row서울특별시 동작구 서달로10라길 16 (흑석동)
ValueCountFrequency (%)
서울특별시 294
20.8%
동작구 293
20.8%
사당동 72
 
5.1%
상도동 48
 
3.4%
신대방동 29
 
2.1%
흑석동 22
 
1.6%
노량진동 21
 
1.5%
대방동 19
 
1.3%
상도1동 12
 
0.9%
동작대로29길 9
 
0.6%
Other values (302) 592
42.0%
2023-12-12T08:19:16.083623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1118
 
15.9%
동 565
 
8.0%
작 325
 
4.6%
서 309
 
4.4%
울 294
 
4.2%
특 294
 
4.2%
별 294
 
4.2%
시 294
 
4.2%
구 294
 
4.2%
로 253
 
3.6%
Other values (67) 3009
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4439
63.0%
Space Separator 1118
 
15.9%
Decimal Number 1054
 
15.0%
Open Punctuation 230
 
3.3%
Close Punctuation 188
 
2.7%
Dash Punctuation 20
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 565
12.7%
작 325
 
7.3%
서 309
 
7.0%
울 294
 
6.6%
특 294
 
6.6%
별 294
 
6.6%
시 294
 
6.6%
구 294
 
6.6%
로 253
 
5.7%
길 247
 
5.6%
Other values (53) 1270
28.6%
Decimal Number
ValueCountFrequency (%)
1 213
20.2%
2 196
18.6%
3 116
11.0%
4 94
8.9%
6 89
8.4%
5 76
 
7.2%
9 72
 
6.8%
7 69
 
6.5%
0 66
 
6.3%
8 63
 
6.0%
Space Separator
ValueCountFrequency (%)
1118
100.0%
Open Punctuation
ValueCountFrequency (%)
( 230
100.0%
Close Punctuation
ValueCountFrequency (%)
) 188
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4439
63.0%
Common 2610
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 565
12.7%
작 325
 
7.3%
서 309
 
7.0%
울 294
 
6.6%
특 294
 
6.6%
별 294
 
6.6%
시 294
 
6.6%
구 294
 
6.6%
로 253
 
5.7%
길 247
 
5.6%
Other values (53) 1270
28.6%
Common
ValueCountFrequency (%)
1118
42.8%
( 230
 
8.8%
1 213
 
8.2%
2 196
 
7.5%
) 188
 
7.2%
3 116
 
4.4%
4 94
 
3.6%
6 89
 
3.4%
5 76
 
2.9%
9 72
 
2.8%
Other values (4) 218
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4439
63.0%
ASCII 2610
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1118
42.8%
( 230
 
8.8%
1 213
 
8.2%
2 196
 
7.5%
) 188
 
7.2%
3 116
 
4.4%
4 94
 
3.6%
6 89
 
3.4%
5 76
 
2.9%
9 72
 
2.8%
Other values (4) 218
 
8.4%
Hangul
ValueCountFrequency (%)
동 565
12.7%
작 325
 
7.3%
서 309
 
7.0%
울 294
 
6.6%
특 294
 
6.6%
별 294
 
6.6%
시 294
 
6.6%
구 294
 
6.6%
로 253
 
5.7%
길 247
 
5.6%
Other values (53) 1270
28.6%

도로명우편번호
Text

MISSING 

Distinct189
Distinct (%)66.5%
Missing255
Missing (%)47.3%
Memory size4.3 KiB
2023-12-12T08:19:16.443940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length4
Mean length7.4084507
Min length3

Characters and Unicode

Total characters2104
Distinct characters120
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

Unique131 ?
Unique (%)46.1%

Sample

1st row7007
2nd row7008
3rd row7011
4th row6985
5th row7015
ValueCountFrequency (%)
1층 35
 
7.8%
사당동 16
 
3.6%
상도동 16
 
3.6%
신대방동 13
 
2.9%
상가동 12
 
2.7%
상가 7
 
1.6%
대방동 6
 
1.3%
노량진동 5
 
1.1%
6980 5
 
1.1%
동작구 4
 
0.9%
Other values (215) 327
73.3%
2023-12-12T08:19:16.917791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
239
 
11.4%
0 180
 
8.6%
1 166
 
7.9%
6 125
 
5.9%
7 119
 
5.7%
9 118
 
5.6%
동 104
 
4.9%
) 89
 
4.2%
( 75
 
3.6%
2 70
 
3.3%
Other values (110) 819
38.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 983
46.7%
Other Letter 702
33.4%
Space Separator 239
 
11.4%
Close Punctuation 89
 
4.2%
Open Punctuation 75
 
3.6%
Uppercase Letter 8
 
0.4%
Dash Punctuation 5
 
0.2%
Lowercase Letter 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 104
 
14.8%
상 63
 
9.0%
호 60
 
8.5%
층 55
 
7.8%
가 44
 
6.3%
대 26
 
3.7%
방 21
 
3.0%
아 20
 
2.8%
사 20
 
2.8%
당 19
 
2.7%
Other values (91) 270
38.5%
Decimal Number
ValueCountFrequency (%)
0 180
18.3%
1 166
16.9%
6 125
12.7%
7 119
12.1%
9 118
12.0%
2 70
 
7.1%
3 69
 
7.0%
5 54
 
5.5%
4 44
 
4.5%
8 38
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
B 4
50.0%
A 4
50.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
239
100.0%
Close Punctuation
ValueCountFrequency (%)
) 89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1392
66.2%
Hangul 702
33.4%
Latin 10
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 104
 
14.8%
상 63
 
9.0%
호 60
 
8.5%
층 55
 
7.8%
가 44
 
6.3%
대 26
 
3.7%
방 21
 
3.0%
아 20
 
2.8%
사 20
 
2.8%
당 19
 
2.7%
Other values (91) 270
38.5%
Common
ValueCountFrequency (%)
239
17.2%
0 180
12.9%
1 166
11.9%
6 125
9.0%
7 119
8.5%
9 118
8.5%
) 89
 
6.4%
( 75
 
5.4%
2 70
 
5.0%
3 69
 
5.0%
Other values (5) 142
10.2%
Latin
ValueCountFrequency (%)
B 4
40.0%
A 4
40.0%
a 1
 
10.0%
e 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1402
66.6%
Hangul 702
33.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
239
17.0%
0 180
12.8%
1 166
11.8%
6 125
8.9%
7 119
8.5%
9 118
8.4%
) 89
 
6.3%
( 75
 
5.3%
2 70
 
5.0%
3 69
 
4.9%
Other values (9) 152
10.8%
Hangul
ValueCountFrequency (%)
동 104
 
14.8%
상 63
 
9.0%
호 60
 
8.5%
층 55
 
7.8%
가 44
 
6.3%
대 26
 
3.7%
방 21
 
3.0%
아 20
 
2.8%
사 20
 
2.8%
당 19
 
2.7%
Other values (91) 270
38.5%

사업장명
Text

Distinct406
Distinct (%)76.0%
Missing5
Missing (%)0.9%
Memory size4.3 KiB
2023-12-12T08:19:17.259920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length4.6685393
Min length2

Characters and Unicode

Total characters2493
Distinct characters270
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

Unique331 ?
Unique (%)62.0%

Sample

1st row소망세탁
2nd row상미세탁소
3rd row백양사
4th row대림사
5th row백미사
ValueCountFrequency (%)
백양사 9
 
1.6%
현대사 8
 
1.4%
백조사 8
 
1.4%
경일사 7
 
1.2%
백양세탁소 6
 
1.1%
세탁소 6
 
1.1%
제일사 5
 
0.9%
6990 4
 
0.7%
현대세탁소 4
 
0.7%
백영사 4
 
0.7%
Other values (417) 504
89.2%
2023-12-12T08:19:17.797153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 175
 
7.0%
세 159
 
6.4%
탁 156
 
6.3%
소 99
 
4.0%
리 66
 
2.6%
백 62
 
2.5%
9 62
 
2.5%
크 62
 
2.5%
6 60
 
2.4%
56
 
2.2%
Other values (260) 1536
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2058
82.6%
Decimal Number 333
 
13.4%
Space Separator 56
 
2.2%
Close Punctuation 28
 
1.1%
Uppercase Letter 7
 
0.3%
Open Punctuation 5
 
0.2%
Lowercase Letter 3
 
0.1%
Other Punctuation 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 175
 
8.5%
세 159
 
7.7%
탁 156
 
7.6%
소 99
 
4.8%
리 66
 
3.2%
백 62
 
3.0%
크 62
 
3.0%
성 53
 
2.6%
닝 47
 
2.3%
미 37
 
1.8%
Other values (237) 1142
55.5%
Decimal Number
ValueCountFrequency (%)
9 62
18.6%
6 60
18.0%
0 51
15.3%
7 48
14.4%
1 30
9.0%
4 24
 
7.2%
2 17
 
5.1%
5 15
 
4.5%
3 14
 
4.2%
8 12
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 2
28.6%
G 2
28.6%
L 2
28.6%
M 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
r 1
33.3%
k 1
33.3%
o 1
33.3%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2058
82.6%
Common 425
 
17.0%
Latin 10
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 175
 
8.5%
세 159
 
7.7%
탁 156
 
7.6%
소 99
 
4.8%
리 66
 
3.2%
백 62
 
3.0%
크 62
 
3.0%
성 53
 
2.6%
닝 47
 
2.3%
미 37
 
1.8%
Other values (237) 1142
55.5%
Common
ValueCountFrequency (%)
9 62
14.6%
6 60
14.1%
56
13.2%
0 51
12.0%
7 48
11.3%
1 30
7.1%
) 28
6.6%
4 24
 
5.6%
2 17
 
4.0%
5 15
 
3.5%
Other values (6) 34
8.0%
Latin
ValueCountFrequency (%)
A 2
20.0%
G 2
20.0%
L 2
20.0%
r 1
10.0%
k 1
10.0%
o 1
10.0%
M 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2058
82.6%
ASCII 435
 
17.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 175
 
8.5%
세 159
 
7.7%
탁 156
 
7.6%
소 99
 
4.8%
리 66
 
3.2%
백 62
 
3.0%
크 62
 
3.0%
성 53
 
2.6%
닝 47
 
2.3%
미 37
 
1.8%
Other values (237) 1142
55.5%
ASCII
ValueCountFrequency (%)
9 62
14.3%
6 60
13.8%
56
12.9%
0 51
11.7%
7 48
11.0%
1 30
6.9%
) 28
6.4%
4 24
 
5.5%
2 17
 
3.9%
5 15
 
3.4%
Other values (13) 44
10.1%

데이터갱신구분
Text

Distinct74
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-12T08:19:18.078082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length1
Mean length2.6938776
Min length1

Characters and Unicode

Total characters1452
Distinct characters72
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)10.4%

Sample

1st rowI
2nd rowI
3rd rowI
4th rowI
5th rowI
ValueCountFrequency (%)
i 344
63.4%
u 84
 
15.5%
2.01907e+13 13
 
2.4%
2.01507e+13 10
 
1.8%
2.0191e+13 3
 
0.6%
2.02011e+13 3
 
0.6%
2.0201e+13 3
 
0.6%
2.02006e+13 3
 
0.6%
2.01901e+13 2
 
0.4%
세탁소 2
 
0.4%
Other values (67) 76
 
14.0%
2023-12-12T08:19:18.454773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
I 344
23.7%
1 182
12.5%
0 158
10.9%
2 108
 
7.4%
3 84
 
5.8%
U 84
 
5.8%
. 79
 
5.4%
E 79
 
5.4%
+ 79
 
5.4%
7 34
 
2.3%
Other values (62) 221
15.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 643
44.3%
Uppercase Letter 509
35.1%
Other Letter 137
 
9.4%
Other Punctuation 79
 
5.4%
Math Symbol 79
 
5.4%
Space Separator 4
 
0.3%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 21
 
15.3%
탁 21
 
15.3%
소 10
 
7.3%
아 5
 
3.6%
성 4
 
2.9%
품 4
 
2.9%
크 4
 
2.9%
명 4
 
2.9%
리 3
 
2.2%
보 3
 
2.2%
Other values (43) 58
42.3%
Decimal Number
ValueCountFrequency (%)
1 182
28.3%
0 158
24.6%
2 108
16.8%
3 84
13.1%
7 34
 
5.3%
9 32
 
5.0%
5 17
 
2.6%
6 12
 
1.9%
8 9
 
1.4%
4 7
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
I 344
67.6%
U 84
 
16.5%
E 79
 
15.5%
L 1
 
0.2%
G 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 79
100.0%
Math Symbol
ValueCountFrequency (%)
+ 79
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 806
55.5%
Latin 509
35.1%
Hangul 137
 
9.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 21
 
15.3%
탁 21
 
15.3%
소 10
 
7.3%
아 5
 
3.6%
성 4
 
2.9%
품 4
 
2.9%
크 4
 
2.9%
명 4
 
2.9%
리 3
 
2.2%
보 3
 
2.2%
Other values (43) 58
42.3%
Common
ValueCountFrequency (%)
1 182
22.6%
0 158
19.6%
2 108
13.4%
3 84
10.4%
. 79
9.8%
+ 79
9.8%
7 34
 
4.2%
9 32
 
4.0%
5 17
 
2.1%
6 12
 
1.5%
Other values (4) 21
 
2.6%
Latin
ValueCountFrequency (%)
I 344
67.6%
U 84
 
16.5%
E 79
 
15.5%
L 1
 
0.2%
G 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1315
90.6%
Hangul 137
 
9.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
I 344
26.2%
1 182
13.8%
0 158
12.0%
2 108
 
8.2%
3 84
 
6.4%
U 84
 
6.4%
. 79
 
6.0%
E 79
 
6.0%
+ 79
 
6.0%
7 34
 
2.6%
Other values (9) 84
 
6.4%
Hangul
ValueCountFrequency (%)
세 21
 
15.3%
탁 21
 
15.3%
소 10
 
7.3%
아 5
 
3.6%
성 4
 
2.9%
품 4
 
2.9%
크 4
 
2.9%
명 4
 
2.9%
리 3
 
2.2%
보 3
 
2.2%
Other values (43) 58
42.3%

업태구분명
Categorical

IMBALANCE 

Distinct23
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
일반세탁업
419 
59:59.0
 
38
40:00.0
 
25
U
 
15
I
 
11
Other values (18)
 
31

Length

Max length11
Median length5
Mean length5.1818182
Min length1

Unique

Unique13 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 419
77.7%
59:59.0 38
 
7.1%
40:00.0 25
 
4.6%
U 15
 
2.8%
I 11
 
2.0%
운동화전문세탁업 7
 
1.3%
07:00.0 3
 
0.6%
08:00.0 3
 
0.6%
04:00.0 3
 
0.6%
00:00.0 2
 
0.4%
Other values (13) 13
 
2.4%

Length

2023-12-12T08:19:18.600727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반세탁업 419
77.6%
59:59.0 38
 
7.0%
40:00.0 25
 
4.6%
u 15
 
2.8%
i 11
 
2.0%
운동화전문세탁업 7
 
1.3%
07:00.0 3
 
0.6%
08:00.0 3
 
0.6%
04:00.0 3
 
0.6%
00:00.0 2
 
0.4%
Other values (14) 14
 
2.6%

좌표정보(X)
Text

MISSING 

Distinct338
Distinct (%)69.3%
Missing51
Missing (%)9.5%
Memory size4.3 KiB
2023-12-12T08:19:18.889508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length9.6413934
Min length1

Characters and Unicode

Total characters4705
Distinct characters31
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique286 ?
Unique (%)58.6%

Sample

1st row197991.3061
2nd row198196.6725
3rd row197390.1432
4th row195684.9734
5th row196447.2009
ValueCountFrequency (%)
일반세탁업 72
 
14.8%
59:59.0 10
 
2.0%
빨래방업 6
 
1.2%
192113.2006 4
 
0.8%
40:00.0 4
 
0.8%
08:00.0 4
 
0.8%
193827.3249 3
 
0.6%
i 3
 
0.6%
195312.3188 3
 
0.6%
197412.7468 3
 
0.6%
Other values (328) 376
77.0%
2023-12-12T08:19:19.295262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 667
14.2%
1 648
13.8%
. 404
8.6%
3 357
7.6%
4 352
7.5%
6 326
6.9%
7 322
6.8%
5 309
6.6%
2 301
6.4%
8 300
6.4%
Other values (21) 719
15.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3873
82.3%
Other Punctuation 430
 
9.1%
Other Letter 396
 
8.4%
Uppercase Letter 5
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 79
19.9%
세 74
18.7%
탁 74
18.7%
반 72
18.2%
일 72
18.2%
방 6
 
1.5%
래 6
 
1.5%
빨 6
 
1.5%
하 1
 
0.3%
얀 1
 
0.3%
Other values (5) 5
 
1.3%
Decimal Number
ValueCountFrequency (%)
9 667
17.2%
1 648
16.7%
3 357
9.2%
4 352
9.1%
6 326
8.4%
7 322
8.3%
5 309
8.0%
2 301
7.8%
8 300
7.7%
0 291
7.5%
Uppercase Letter
ValueCountFrequency (%)
I 3
60.0%
E 1
 
20.0%
U 1
 
20.0%
Other Punctuation
ValueCountFrequency (%)
. 404
94.0%
: 26
 
6.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4304
91.5%
Hangul 396
 
8.4%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 79
19.9%
세 74
18.7%
탁 74
18.7%
반 72
18.2%
일 72
18.2%
방 6
 
1.5%
래 6
 
1.5%
빨 6
 
1.5%
하 1
 
0.3%
얀 1
 
0.3%
Other values (5) 5
 
1.3%
Common
ValueCountFrequency (%)
9 667
15.5%
1 648
15.1%
. 404
9.4%
3 357
8.3%
4 352
8.2%
6 326
7.6%
7 322
7.5%
5 309
7.2%
2 301
7.0%
8 300
7.0%
Other values (3) 318
7.4%
Latin
ValueCountFrequency (%)
I 3
60.0%
E 1
 
20.0%
U 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4309
91.6%
Hangul 396
 
8.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 667
15.5%
1 648
15.0%
. 404
9.4%
3 357
8.3%
4 352
8.2%
6 326
7.6%
7 322
7.5%
5 309
7.2%
2 301
7.0%
8 300
7.0%
Other values (6) 323
7.5%
Hangul
ValueCountFrequency (%)
업 79
19.9%
세 74
18.7%
탁 74
18.7%
반 72
18.2%
일 72
18.2%
방 6
 
1.5%
래 6
 
1.5%
빨 6
 
1.5%
하 1
 
0.3%
얀 1
 
0.3%
Other values (5) 5
 
1.3%

좌표정보(Y)
Text

MISSING 

Distinct398
Distinct (%)81.6%
Missing51
Missing (%)9.5%
Memory size4.3 KiB
2023-12-12T08:19:19.537571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.520492
Min length1

Characters and Unicode

Total characters5134
Distinct characters20
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique346 ?
Unique (%)70.9%

Sample

1st row442558.1048
2nd row442623.1074
3rd row442578.0473
4th row444497.8167
5th row444462.6339
ValueCountFrequency (%)
일반세탁업 26
 
5.3%
197802.0549 4
 
0.8%
443344.3735 4
 
0.8%
442064.8007 3
 
0.6%
443352.6725 3
 
0.6%
442578.0473 3
 
0.6%
444497.8167 3
 
0.6%
443168.5136 3
 
0.6%
443472.2052 3
 
0.6%
444456.4943 3
 
0.6%
Other values (388) 433
88.7%
2023-12-12T08:19:19.906230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1198
23.3%
. 461
 
9.0%
2 427
 
8.3%
3 422
 
8.2%
1 415
 
8.1%
9 378
 
7.4%
5 375
 
7.3%
8 356
 
6.9%
6 341
 
6.6%
7 340
 
6.6%
Other values (10) 421
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4536
88.4%
Other Punctuation 465
 
9.1%
Other Letter 130
 
2.5%
Uppercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1198
26.4%
2 427
 
9.4%
3 422
 
9.3%
1 415
 
9.1%
9 378
 
8.3%
5 375
 
8.3%
8 356
 
7.8%
6 341
 
7.5%
7 340
 
7.5%
0 284
 
6.3%
Other Letter
ValueCountFrequency (%)
일 26
20.0%
반 26
20.0%
업 26
20.0%
탁 26
20.0%
세 26
20.0%
Other Punctuation
ValueCountFrequency (%)
. 461
99.1%
: 4
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
I 1
50.0%
E 1
50.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5002
97.4%
Hangul 130
 
2.5%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1198
24.0%
. 461
 
9.2%
2 427
 
8.5%
3 422
 
8.4%
1 415
 
8.3%
9 378
 
7.6%
5 375
 
7.5%
8 356
 
7.1%
6 341
 
6.8%
7 340
 
6.8%
Other values (3) 289
 
5.8%
Hangul
ValueCountFrequency (%)
일 26
20.0%
반 26
20.0%
업 26
20.0%
탁 26
20.0%
세 26
20.0%
Latin
ValueCountFrequency (%)
I 1
50.0%
E 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5004
97.5%
Hangul 130
 
2.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1198
23.9%
. 461
 
9.2%
2 427
 
8.5%
3 422
 
8.4%
1 415
 
8.3%
9 378
 
7.6%
5 375
 
7.5%
8 356
 
7.1%
6 341
 
6.8%
7 340
 
6.8%
Other values (5) 291
 
5.8%
Hangul
ValueCountFrequency (%)
일 26
20.0%
반 26
20.0%
업 26
20.0%
탁 26
20.0%
세 26
20.0%

위생업태명
Text

MISSING 

Distinct98
Distinct (%)19.1%
Missing26
Missing (%)4.8%
Memory size4.3 KiB
2023-12-12T08:19:20.220065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length5
Mean length6.2417154
Min length1

Characters and Unicode

Total characters3202
Distinct characters29
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)16.6%

Sample

1st row일반세탁업
2nd row일반세탁업
3rd row일반세탁업
4th row일반세탁업
5th row일반세탁업
ValueCountFrequency (%)
일반세탁업 397
77.2%
운동화전문세탁업 7
 
1.4%
443049.4715 4
 
0.8%
197802.0549 2
 
0.4%
444431.008 2
 
0.4%
441846.7135 2
 
0.4%
191691.6784 2
 
0.4%
193204.7822 2
 
0.4%
445602.1324 2
 
0.4%
195585.914 2
 
0.4%
Other values (89) 92
 
17.9%
2023-12-12T08:19:20.666868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 406
12.7%
세 405
12.6%
탁 405
12.6%
일 397
12.4%
반 397
12.4%
4 271
8.5%
1 114
 
3.6%
. 106
 
3.3%
3 105
 
3.3%
9 102
 
3.2%
Other values (19) 494
15.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2050
64.0%
Decimal Number 1043
32.6%
Other Punctuation 107
 
3.3%
Uppercase Letter 1
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 406
19.8%
세 405
19.8%
탁 405
19.8%
일 397
19.4%
반 397
19.4%
문 7
 
0.3%
전 7
 
0.3%
운 7
 
0.3%
동 7
 
0.3%
화 7
 
0.3%
Other values (5) 5
 
0.2%
Decimal Number
ValueCountFrequency (%)
4 271
26.0%
1 114
10.9%
3 105
 
10.1%
9 102
 
9.8%
5 98
 
9.4%
2 79
 
7.6%
6 72
 
6.9%
8 70
 
6.7%
7 69
 
6.6%
0 63
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 106
99.1%
: 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
I 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2050
64.0%
Common 1151
35.9%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 406
19.8%
세 405
19.8%
탁 405
19.8%
일 397
19.4%
반 397
19.4%
문 7
 
0.3%
전 7
 
0.3%
운 7
 
0.3%
동 7
 
0.3%
화 7
 
0.3%
Other values (5) 5
 
0.2%
Common
ValueCountFrequency (%)
4 271
23.5%
1 114
9.9%
. 106
 
9.2%
3 105
 
9.1%
9 102
 
8.9%
5 98
 
8.5%
2 79
 
6.9%
6 72
 
6.3%
8 70
 
6.1%
7 69
 
6.0%
Other values (3) 65
 
5.6%
Latin
ValueCountFrequency (%)
I 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2050
64.0%
ASCII 1152
36.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 406
19.8%
세 405
19.8%
탁 405
19.8%
일 397
19.4%
반 397
19.4%
문 7
 
0.3%
전 7
 
0.3%
운 7
 
0.3%
동 7
 
0.3%
화 7
 
0.3%
Other values (5) 5
 
0.2%
ASCII
ValueCountFrequency (%)
4 271
23.5%
1 114
9.9%
. 106
 
9.2%
3 105
 
9.1%
9 102
 
8.9%
5 98
 
8.5%
2 79
 
6.9%
6 72
 
6.2%
8 70
 
6.1%
7 69
 
6.0%
Other values (4) 66
 
5.7%

건물지상층수
Categorical

IMBALANCE 

Distinct37
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
241 
0
139 
일반세탁업
60 
3
27 
2
 
11
Other values (32)
61 

Length

Max length11
Median length10
Mean length3.3858998
Min length1

Unique

Unique21 ?
Unique (%)3.9%

Sample

1st row2
2nd row5
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 241
44.7%
0 139
25.8%
일반세탁업 60
 
11.1%
3 27
 
5.0%
2 11
 
2.0%
4 10
 
1.9%
1 8
 
1.5%
5 4
 
0.7%
빨래방업 4
 
0.7%
443690.5954 2
 
0.4%
Other values (27) 33
 
6.1%

Length

2023-12-12T08:19:20.863050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 241
44.7%
0 139
25.8%
일반세탁업 60
 
11.1%
3 27
 
5.0%
2 11
 
2.0%
4 10
 
1.9%
1 8
 
1.5%
5 4
 
0.7%
빨래방업 4
 
0.7%
443168.5136 2
 
0.4%
Other values (27) 33
 
6.1%

건물지하층수
Categorical

IMBALANCE 

Distinct13
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
286 
0
174 
1
43 
일반세탁업
 
17
4
 
5
Other values (8)
 
14

Length

Max length11
Median length4
Mean length2.8089054
Min length1

Unique

Unique4 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 286
53.1%
0 174
32.3%
1 43
 
8.0%
일반세탁업 17
 
3.2%
4 5
 
0.9%
3 3
 
0.6%
2 3
 
0.6%
445024.4852 2
 
0.4%
5 2
 
0.4%
195669.6798 1
 
0.2%
Other values (3) 3
 
0.6%

Length

2023-12-12T08:19:21.055466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 286
53.1%
0 174
32.3%
1 43
 
8.0%
일반세탁업 17
 
3.2%
4 5
 
0.9%
3 3
 
0.6%
2 3
 
0.6%
445024.4852 2
 
0.4%
5 2
 
0.4%
195669.6798 1
 
0.2%
Other values (3) 3
 
0.6%

사용시작지상층
Categorical

Distinct9
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
259 
0
164 
1
96 
2
 
9
일반세탁업
 
4
Other values (4)
 
7

Length

Max length11
Median length1
Mean length2.5064935
Min length1

Unique

Unique3 ?
Unique (%)0.6%

Sample

1st row1
2nd row1
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 259
48.1%
0 164
30.4%
1 96
 
17.8%
2 9
 
1.7%
일반세탁업 4
 
0.7%
3 4
 
0.7%
445275.208 1
 
0.2%
4 1
 
0.2%
195078.2362 1
 
0.2%

Length

2023-12-12T08:19:21.200344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:21.354340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 259
48.1%
0 164
30.4%
1 96
 
17.8%
2 9
 
1.7%
일반세탁업 4
 
0.7%
3 4
 
0.7%
445275.208 1
 
0.2%
4 1
 
0.2%
195078.2362 1
 
0.2%

사용끝지상층
Categorical

Distinct8
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
283 
0
147 
1
90 
2
 
11
4
 
3
Other values (3)
 
5

Length

Max length11
Median length4
Mean length2.6011132
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row1
2nd row1
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 283
52.5%
0 147
27.3%
1 90
 
16.7%
2 11
 
2.0%
4 3
 
0.6%
3 3
 
0.6%
일반세탁업 1
 
0.2%
445024.4852 1
 
0.2%

Length

2023-12-12T08:19:21.534522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:21.685252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 283
52.5%
0 147
27.3%
1 90
 
16.7%
2 11
 
2.0%
4 3
 
0.6%
3 3
 
0.6%
일반세탁업 1
 
0.2%
445024.4852 1
 
0.2%

사용시작지하층
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
369 
0
137 
1
 
18
3
 
7
2
 
5
Other values (2)
 
3

Length

Max length5
Median length4
Mean length3.0612245
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 369
68.5%
0 137
 
25.4%
1 18
 
3.3%
3 7
 
1.3%
2 5
 
0.9%
4 2
 
0.4%
일반세탁업 1
 
0.2%

Length

2023-12-12T08:19:21.864701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:22.005822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 369
68.5%
0 137
 
25.4%
1 18
 
3.3%
3 7
 
1.3%
2 5
 
0.9%
4 2
 
0.4%
일반세탁업 1
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
383 
0
139 
1
 
13
4
 
2
2
 
1

Length

Max length4
Median length4
Mean length3.1317254
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 383
71.1%
0 139
 
25.8%
1 13
 
2.4%
4 2
 
0.4%
2 1
 
0.2%
3 1
 
0.2%

Length

2023-12-12T08:19:22.127817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:22.281811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 383
71.1%
0 139
 
25.8%
1 13
 
2.4%
4 2
 
0.4%
2 1
 
0.2%
3 1
 
0.2%

한실수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
367 
0
165 
1
 
5
3
 
2

Length

Max length4
Median length4
Mean length3.0426716
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 367
68.1%
0 165
30.6%
1 5
 
0.9%
3 2
 
0.4%

Length

2023-12-12T08:19:22.430337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:22.567473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 367
68.1%
0 165
30.6%
1 5
 
0.9%
3 2
 
0.4%

양실수
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
352 
0
186 
1
 
1

Length

Max length4
Median length4
Mean length2.9591837
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 352
65.3%
0 186
34.5%
1 1
 
0.2%

Length

2023-12-12T08:19:22.731669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:22.848650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 352
65.3%
0 186
34.5%
1 1
 
0.2%

욕실수
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
341 
0
197 
1
 
1

Length

Max length4
Median length4
Mean length2.8979592
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 341
63.3%
0 197
36.5%
1 1
 
0.2%

Length

2023-12-12T08:19:22.959631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:23.063474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 341
63.3%
0 197
36.5%
1 1
 
0.2%

발한실여부
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
N
398 
<NA>
99 
0
42 

Length

Max length4
Median length1
Mean length1.5510204
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 398
73.8%
<NA> 99
 
18.4%
0 42
 
7.8%

Length

2023-12-12T08:19:23.167456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:23.259292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 398
73.8%
na 99
 
18.4%
0 42
 
7.8%

좌석수
Categorical

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
306 
0
169 
N
63 
2
 
1

Length

Max length4
Median length4
Mean length2.703154
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 306
56.8%
0 169
31.4%
N 63
 
11.7%
2 1
 
0.2%

Length

2023-12-12T08:19:23.357316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:23.449123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 306
56.8%
0 169
31.4%
n 63
 
11.7%
2 1
 
0.2%

조건부허가신고사유
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
492 
0
 
30
N
 
16
2
 
1

Length

Max length4
Median length4
Mean length3.7384045
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 492
91.3%
0 30
 
5.6%
N 16
 
3.0%
2 1
 
0.2%

Length

2023-12-12T08:19:23.566477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:23.696600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 492
91.3%
0 30
 
5.6%
n 16
 
3.0%
2 1
 
0.2%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
523 
0
 
12
N
 
4

Length

Max length4
Median length4
Mean length3.9109462
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> 523
97.0%
0 12
 
2.2%
N 4
 
0.7%

Length

2023-12-12T08:19:23.791720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:23.883835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 523
97.0%
0 12
 
2.2%
n 4
 
0.7%

조건부허가종료일자
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing537
Missing (%)99.6%
Memory size4.3 KiB
2023-12-12T08:19:24.193579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowN
2nd row0
ValueCountFrequency (%)
n 1
50.0%
0 1
50.0%
2023-12-12T08:19:24.410492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1
50.0%
0 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1
50.0%
Decimal Number 1
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%
Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1
50.0%
Common 1
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1
100.0%
Common
ValueCountFrequency (%)
0 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1
50.0%
0 1
50.0%

건물소유구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
482 
임대
54 
자가
 
2
N
 
1

Length

Max length4
Median length4
Mean length3.7866419
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 482
89.4%
임대 54
 
10.0%
자가 2
 
0.4%
N 1
 
0.2%

Length

2023-12-12T08:19:24.536076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:24.640732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 482
89.4%
임대 54
 
10.0%
자가 2
 
0.4%
n 1
 
0.2%

세탁기수
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
420 
1
80 
임대
 
14
0
 
10
2
 
9
Other values (2)
 
6

Length

Max length4
Median length4
Mean length3.3636364
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 420
77.9%
1 80
 
14.8%
임대 14
 
2.6%
0 10
 
1.9%
2 9
 
1.7%
3 4
 
0.7%
4 2
 
0.4%

Length

2023-12-12T08:19:24.748454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:24.840583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 420
77.9%
1 80
 
14.8%
임대 14
 
2.6%
0 10
 
1.9%
2 9
 
1.7%
3 4
 
0.7%
4 2
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct9
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
490 
1
 
30
2
 
9
3
 
4
4
 
2
Other values (4)
 
4

Length

Max length4
Median length4
Mean length3.7309833
Min length1

Unique

Unique4 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 490
90.9%
1 30
 
5.6%
2 9
 
1.7%
3 4
 
0.7%
4 2
 
0.4%
0 1
 
0.2%
임대 1
 
0.2%
31 1
 
0.2%
5 1
 
0.2%

Length

2023-12-12T08:19:24.941366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:25.040374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 490
90.9%
1 30
 
5.6%
2 9
 
1.7%
3 4
 
0.7%
4 2
 
0.4%
0 1
 
0.2%
임대 1
 
0.2%
31 1
 
0.2%
5 1
 
0.2%

남성종사자수
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
517 
1
 
8
0
 
7
2
 
3
임대
 
2
Other values (2)
 
2

Length

Max length4
Median length4
Mean length3.8812616
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 517
95.9%
1 8
 
1.5%
0 7
 
1.3%
2 3
 
0.6%
임대 2
 
0.4%
3 1
 
0.2%
4 1
 
0.2%

Length

2023-12-12T08:19:25.141395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:25.228882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 517
95.9%
1 8
 
1.5%
0 7
 
1.3%
2 3
 
0.6%
임대 2
 
0.4%
3 1
 
0.2%
4 1
 
0.2%

회수건조수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
474 
1
49 
0
 
15
3
 
1

Length

Max length4
Median length4
Mean length3.6382189
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 474
87.9%
1 49
 
9.1%
0 15
 
2.8%
3 1
 
0.2%

Length

2023-12-12T08:19:25.320281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:25.397124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 474
87.9%
1 49
 
9.1%
0 15
 
2.8%
3 1
 
0.2%

침대수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
482 
0
 
30
1
 
26
임대
 
1

Length

Max length4
Median length4
Mean length3.6846011
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 482
89.4%
0 30
 
5.6%
1 26
 
4.8%
임대 1
 
0.2%

Length

2023-12-12T08:19:25.484744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:25.575289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 482
89.4%
0 30
 
5.6%
1 26
 
4.8%
임대 1
 
0.2%

다중이용업소여부
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
N
402 
<NA>
101 
0
 
23
1
 
11
2
 
2

Length

Max length4
Median length1
Mean length1.5621521
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 402
74.6%
<NA> 101
 
18.7%
0 23
 
4.3%
1 11
 
2.0%
2 2
 
0.4%

Length

2023-12-12T08:19:25.665399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:19:25.750952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 402
74.6%
na 101
 
18.7%
0 23
 
4.3%
1 11
 
2.0%
2 2
 
0.4%

Sample

관리번호인허가일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명데이터갱신구분업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
03190000-205-1987-016751987-06-011영업/정상1영업<NA>19.0156816.0서울특별시 동작구 사당동 141-156번지서울특별시 동작구 사당로27길 24 (사당동)7007소망세탁I일반세탁업197991.3061442558.1048일반세탁업2<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대1<NA><NA>1<NA>N
13190000-205-1987-016761987-06-013폐업2폐업2014-10-1635.69156824.0서울특별시 동작구 사당동 708-457번지서울특별시 동작구 동작대로27다길 41 (사당동)7008상미세탁소I일반세탁업198196.6725442623.1074일반세탁업5<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
23190000-205-1987-016771987-06-013폐업2폐업2003-06-050.0156090.0서울특별시 동작구 사당동 1131-0번지 영아A 상가 203호<NA><NA>백양사I일반세탁업197390.1432442578.0473일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
33190000-205-1987-016781987-06-193폐업2폐업1997-07-10494.8156834.0서울특별시 동작구 상도1동 326-14번지<NA><NA>대림사I일반세탁업195684.9734444497.8167일반세탁업000000000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
43190000-205-1987-016791987-06-193폐업2폐업2007-06-040.0156858.0서울특별시 동작구 흑석동 79-93번지<NA><NA>백미사I일반세탁업196447.2009444462.6339일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
53190000-205-1987-016801987-09-013폐업2폐업2004-11-010.0156030.0서울특별시 동작구 상도동 67-6번지<NA><NA>국제크리닝I일반세탁업195729.8677444060.5957일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
63190000-205-1987-016951987-06-013폐업2폐업2019-12-0319.9156821.0서울특별시 동작구 사당동 312-7번지서울특별시 동작구 사당로16길 57 (사당동)7011상신세탁소U일반세탁업197470.6843442103.2558일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA>1<NA><NA>1<NA>N
73190000-205-1987-016961987-06-013폐업2폐업2015-09-0132.64156824.0서울특별시 동작구 사당동 708-690번지서울특별시 동작구 사당로23길 126 (사당동)<NA>문성사I일반세탁업197530.5195442896.4922일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
83190000-205-1987-016971987-06-013폐업2폐업2000-05-270.0156818.0서울특별시 동작구 사당동 171-1번지<NA><NA>삼성크리닝I일반세탁업<NA><NA>일반세탁업000000000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
93190000-205-1987-016981987-06-013폐업2폐업2002-05-0170.26156818.0서울특별시 동작구 사당동 170-25번지<NA><NA>장미사I일반세탁업197435.0875443040.2828일반세탁업000000000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
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5363190000-205-2019-000052019-10-251영업/정상1영업<NA>22.5156718.0서울특별시 동작구 상도동 414 건영아파트서울특별시 동작구 만양로 26상가동 2층 205호 (상도동건영아파트)우리세탁소U08:00.0일반세탁업195489.4234444995.6756<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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