Overview

Dataset statistics

Number of variables34
Number of observations140
Missing cells1037
Missing cells (%)21.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.9 KiB
Average record size in memory291.9 B

Variable types

Categorical14
Text6
DateTime4
Numeric5
Unsupported5

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),문화체육업종명,공사립구분명,보험가입여부코드,지도자수,건축물동수,건축물연면적,회원모집총인원,세부업종명,법인명
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-19852/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (89.2%)Imbalance
휴업시작일자 is highly imbalanced (93.9%)Imbalance
휴업종료일자 is highly imbalanced (93.9%)Imbalance
보험가입여부코드 is highly imbalanced (60.3%)Imbalance
건축물동수 is highly imbalanced (51.6%)Imbalance
회원모집총인원 is highly imbalanced (85.1%)Imbalance
폐업일자 has 73 (52.1%) missing valuesMissing
재개업일자 has 140 (100.0%) missing valuesMissing
전화번호 has 54 (38.6%) missing valuesMissing
소재지면적 has 140 (100.0%) missing valuesMissing
소재지우편번호 has 81 (57.9%) missing valuesMissing
도로명주소 has 2 (1.4%) missing valuesMissing
도로명우편번호 has 32 (22.9%) missing valuesMissing
업태구분명 has 140 (100.0%) missing valuesMissing
좌표정보(X) has 2 (1.4%) missing valuesMissing
좌표정보(Y) has 2 (1.4%) missing valuesMissing
건축물연면적 has 91 (65.0%) missing valuesMissing
세부업종명 has 140 (100.0%) missing valuesMissing
법인명 has 140 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
세부업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
법인명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건축물연면적 has 25 (17.9%) zerosZeros

Reproduction

Analysis started2024-05-11 00:36:25.312457
Analysis finished2024-05-11 00:36:26.894455
Duration1.58 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3000000
140 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000000
2nd row3000000
3rd row3000000
4th row3000000
5th row3000000

Common Values

ValueCountFrequency (%)
3000000 140
100.0%

Length

2024-05-11T00:36:27.092044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:36:27.372676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000000 140
100.0%

관리번호
Text

UNIQUE 

Distinct140
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T00:36:27.904449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters2800
Distinct characters14
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

Unique140 ?
Unique (%)100.0%

Sample

1st rowCDFH3301061989000001
2nd rowCDFH3301061989000002
3rd rowCDFH3301061990000001
4th rowCDFH3301061992000001
5th rowCDFH3301061992000002
ValueCountFrequency (%)
cdfh3301061989000001 1
 
0.7%
cdfh3301062016000007 1
 
0.7%
cdfh3301062019000005 1
 
0.7%
cdfh3301062019000004 1
 
0.7%
cdfh3301062019000003 1
 
0.7%
cdfh3301062019000002 1
 
0.7%
cdfh3301062019000001 1
 
0.7%
cdfh3301062018000007 1
 
0.7%
cdfh3301062018000006 1
 
0.7%
cdfh3301062016000006 1
 
0.7%
Other values (130) 130
92.9%
2024-05-11T00:36:28.968701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1147
41.0%
3 318
 
11.4%
1 262
 
9.4%
2 199
 
7.1%
6 162
 
5.8%
C 140
 
5.0%
D 140
 
5.0%
F 140
 
5.0%
H 140
 
5.0%
9 67
 
2.4%
Other values (4) 85
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2240
80.0%
Uppercase Letter 560
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1147
51.2%
3 318
 
14.2%
1 262
 
11.7%
2 199
 
8.9%
6 162
 
7.2%
9 67
 
3.0%
4 28
 
1.2%
5 25
 
1.1%
8 19
 
0.8%
7 13
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 140
25.0%
D 140
25.0%
F 140
25.0%
H 140
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2240
80.0%
Latin 560
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1147
51.2%
3 318
 
14.2%
1 262
 
11.7%
2 199
 
8.9%
6 162
 
7.2%
9 67
 
3.0%
4 28
 
1.2%
5 25
 
1.1%
8 19
 
0.8%
7 13
 
0.6%
Latin
ValueCountFrequency (%)
C 140
25.0%
D 140
25.0%
F 140
25.0%
H 140
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1147
41.0%
3 318
 
11.4%
1 262
 
9.4%
2 199
 
7.1%
6 162
 
5.8%
C 140
 
5.0%
D 140
 
5.0%
F 140
 
5.0%
H 140
 
5.0%
9 67
 
2.4%
Other values (4) 85
 
3.0%

인허가일자
Date

Distinct137
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1989-12-30 00:00:00
Maximum2024-04-05 00:00:00
2024-05-11T00:36:29.620508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:36:30.308353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
138 
20150824
 
2

Length

Max length8
Median length4
Mean length4.0571429
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> 138
98.6%
20150824 2
 
1.4%

Length

2024-05-11T00:36:30.887616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:36:31.387214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 138
98.6%
20150824 2
 
1.4%

영업상태코드
Categorical

Distinct5
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1
70 
3
48 
4
20 
2
 
1
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
1 70
50.0%
3 48
34.3%
4 20
 
14.3%
2 1
 
0.7%
5 1
 
0.7%

Length

2024-05-11T00:36:31.941611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:36:32.470540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 70
50.0%
3 48
34.3%
4 20
 
14.3%
2 1
 
0.7%
5 1
 
0.7%

영업상태명
Categorical

Distinct5
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업/정상
70 
폐업
48 
취소/말소/만료/정지/중지
20 
휴업
 
1
제외/삭제/전출
 
1

Length

Max length14
Median length11
Mean length5.2571429
Min length2

Unique

Unique2 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 70
50.0%
폐업 48
34.3%
취소/말소/만료/정지/중지 20
 
14.3%
휴업 1
 
0.7%
제외/삭제/전출 1
 
0.7%

Length

2024-05-11T00:36:33.178418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:36:33.654616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 70
50.0%
폐업 48
34.3%
취소/말소/만료/정지/중지 20
 
14.3%
휴업 1
 
0.7%
제외/삭제/전출 1
 
0.7%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.607143
Minimum2
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T00:36:33.997816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median13
Q313
95-th percentile35
Maximum35
Range33
Interquartile range (IQR)10

Descriptive statistics

Standard deviation10.156117
Coefficient of variation (CV)0.80558435
Kurtosis0.62697742
Mean12.607143
Median Absolute Deviation (MAD)1
Skewness1.2050627
Sum1765
Variance103.14671
MonotonicityNot monotonic
2024-05-11T00:36:34.322043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
13 70
50.0%
3 48
34.3%
35 18
 
12.9%
32 2
 
1.4%
2 1
 
0.7%
15 1
 
0.7%
ValueCountFrequency (%)
2 1
 
0.7%
3 48
34.3%
13 70
50.0%
15 1
 
0.7%
32 2
 
1.4%
35 18
 
12.9%
ValueCountFrequency (%)
35 18
 
12.9%
32 2
 
1.4%
15 1
 
0.7%
13 70
50.0%
3 48
34.3%
2 1
 
0.7%

상세영업상태명
Categorical

Distinct6
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업중
70 
폐업
48 
직권말소
18 
신고취소
 
2
휴업
 
1

Length

Max length4
Median length3.5
Mean length2.7857143
Min length2

Unique

Unique2 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 70
50.0%
폐업 48
34.3%
직권말소 18
 
12.9%
신고취소 2
 
1.4%
휴업 1
 
0.7%
전출 1
 
0.7%

Length

2024-05-11T00:36:34.980618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:36:35.569561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 70
50.0%
폐업 48
34.3%
직권말소 18
 
12.9%
신고취소 2
 
1.4%
휴업 1
 
0.7%
전출 1
 
0.7%

폐업일자
Date

MISSING 

Distinct46
Distinct (%)68.7%
Missing73
Missing (%)52.1%
Memory size1.2 KiB
Minimum1998-09-07 00:00:00
Maximum2024-03-22 00:00:00
2024-05-11T00:36:36.438650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:36:37.152151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
139 
20200323
 
1

Length

Max length8
Median length4
Mean length4.0285714
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 139
99.3%
20200323 1
 
0.7%

Length

2024-05-11T00:36:38.043322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:36:38.477616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 139
99.3%
20200323 1
 
0.7%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
139 
20200922
 
1

Length

Max length8
Median length4
Mean length4.0285714
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 139
99.3%
20200922 1
 
0.7%

Length

2024-05-11T00:36:39.069928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:36:39.514367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 139
99.3%
20200922 1
 
0.7%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

전화번호
Text

MISSING 

Distinct86
Distinct (%)100.0%
Missing54
Missing (%)38.6%
Memory size1.2 KiB
2024-05-11T00:36:40.498503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length10.988372
Min length8

Characters and Unicode

Total characters945
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

Unique86 ?
Unique (%)100.0%

Sample

1st row02-765-4738
2nd row02-763-7715
3rd row02-743-4016
4th row02-742-7953
5th row02-2274-0798
ValueCountFrequency (%)
02-741-2225 1
 
1.2%
02-722-3770 1
 
1.2%
02-3673-3333 1
 
1.2%
02-395-2234 1
 
1.2%
02-396-0653 1
 
1.2%
02-722-3144 1
 
1.2%
02-395-0653 1
 
1.2%
02-2277-2229 1
 
1.2%
02-765-4202 1
 
1.2%
02-744-7561 1
 
1.2%
Other values (76) 76
88.4%
2024-05-11T00:36:42.093602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 161
17.0%
2 158
16.7%
0 128
13.5%
7 118
12.5%
3 96
10.2%
1 65
6.9%
4 55
 
5.8%
6 52
 
5.5%
5 51
 
5.4%
8 31
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 784
83.0%
Dash Punctuation 161
 
17.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 158
20.2%
0 128
16.3%
7 118
15.1%
3 96
12.2%
1 65
8.3%
4 55
 
7.0%
6 52
 
6.6%
5 51
 
6.5%
8 31
 
4.0%
9 30
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 945
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 161
17.0%
2 158
16.7%
0 128
13.5%
7 118
12.5%
3 96
10.2%
1 65
6.9%
4 55
 
5.8%
6 52
 
5.5%
5 51
 
5.4%
8 31
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 945
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 161
17.0%
2 158
16.7%
0 128
13.5%
7 118
12.5%
3 96
10.2%
1 65
6.9%
4 55
 
5.8%
6 52
 
5.5%
5 51
 
5.4%
8 31
 
3.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

소재지우편번호
Text

MISSING 

Distinct42
Distinct (%)71.2%
Missing81
Missing (%)57.9%
Memory size1.2 KiB
2024-05-11T00:36:42.790722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0677966
Min length6

Characters and Unicode

Total characters358
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

Unique28 ?
Unique (%)47.5%

Sample

1st row110825
2nd row110836
3rd row110841
4th row110470
5th row110090
ValueCountFrequency (%)
110470 5
 
8.5%
110040 2
 
3.4%
110846 2
 
3.4%
110522 2
 
3.4%
110880 2
 
3.4%
110110 2
 
3.4%
110825 2
 
3.4%
110111 2
 
3.4%
110123 2
 
3.4%
110809 2
 
3.4%
Other values (32) 36
61.0%
2024-05-11T00:36:43.813467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 147
41.1%
0 97
27.1%
8 23
 
6.4%
2 21
 
5.9%
4 20
 
5.6%
7 13
 
3.6%
3 11
 
3.1%
5 9
 
2.5%
6 8
 
2.2%
9 5
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 354
98.9%
Dash Punctuation 4
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 147
41.5%
0 97
27.4%
8 23
 
6.5%
2 21
 
5.9%
4 20
 
5.6%
7 13
 
3.7%
3 11
 
3.1%
5 9
 
2.5%
6 8
 
2.3%
9 5
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 358
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 147
41.1%
0 97
27.1%
8 23
 
6.4%
2 21
 
5.9%
4 20
 
5.6%
7 13
 
3.6%
3 11
 
3.1%
5 9
 
2.5%
6 8
 
2.2%
9 5
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 358
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 147
41.1%
0 97
27.1%
8 23
 
6.4%
2 21
 
5.9%
4 20
 
5.6%
7 13
 
3.6%
3 11
 
3.1%
5 9
 
2.5%
6 8
 
2.2%
9 5
 
1.4%

지번주소
Text

Distinct134
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T00:36:44.737830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length31
Mean length24.364286
Min length14

Characters and Unicode

Total characters3411
Distinct characters187
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

Unique129 ?
Unique (%)92.1%

Sample

1st row서울특별시 종로구 숭인동 201-5번지
2nd row서울특별시 종로구 종로6가 210-11번지
3rd row서울특별시 종로구 종로5가 182-6번지
4th row서울특별시 종로구 창신동 407-4번지
5th row서울특별시 종로구 종로5가 265-12번지
ValueCountFrequency (%)
서울특별시 140
20.7%
종로구 140
20.7%
내수동 11
 
1.6%
숭인동 10
 
1.5%
평창동 8
 
1.2%
관철동 8
 
1.2%
지하1층 8
 
1.2%
창신동 7
 
1.0%
연지동 6
 
0.9%
종로1가 5
 
0.7%
Other values (253) 334
49.3%
2024-05-11T00:36:46.486135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
629
18.4%
로 173
 
5.1%
종 162
 
4.7%
1 151
 
4.4%
서 145
 
4.3%
시 141
 
4.1%
구 141
 
4.1%
특 140
 
4.1%
별 140
 
4.1%
울 140
 
4.1%
Other values (177) 1449
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2150
63.0%
Space Separator 629
 
18.4%
Decimal Number 536
 
15.7%
Dash Punctuation 81
 
2.4%
Other Punctuation 6
 
0.2%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%
Uppercase Letter 2
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 173
 
8.0%
종 162
 
7.5%
서 145
 
6.7%
시 141
 
6.6%
구 141
 
6.6%
특 140
 
6.5%
별 140
 
6.5%
울 140
 
6.5%
동 115
 
5.3%
지 104
 
4.8%
Other values (160) 749
34.8%
Decimal Number
ValueCountFrequency (%)
1 151
28.2%
2 69
12.9%
0 58
 
10.8%
5 48
 
9.0%
4 45
 
8.4%
3 42
 
7.8%
8 38
 
7.1%
7 32
 
6.0%
6 30
 
5.6%
9 23
 
4.3%
Space Separator
ValueCountFrequency (%)
629
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2150
63.0%
Common 1258
36.9%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 173
 
8.0%
종 162
 
7.5%
서 145
 
6.7%
시 141
 
6.6%
구 141
 
6.6%
특 140
 
6.5%
별 140
 
6.5%
울 140
 
6.5%
동 115
 
5.3%
지 104
 
4.8%
Other values (160) 749
34.8%
Common
ValueCountFrequency (%)
629
50.0%
1 151
 
12.0%
- 81
 
6.4%
2 69
 
5.5%
0 58
 
4.6%
5 48
 
3.8%
4 45
 
3.6%
3 42
 
3.3%
8 38
 
3.0%
7 32
 
2.5%
Other values (5) 65
 
5.2%
Latin
ValueCountFrequency (%)
B 2
66.7%
b 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2150
63.0%
ASCII 1261
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
629
49.9%
1 151
 
12.0%
- 81
 
6.4%
2 69
 
5.5%
0 58
 
4.6%
5 48
 
3.8%
4 45
 
3.6%
3 42
 
3.3%
8 38
 
3.0%
7 32
 
2.5%
Other values (7) 68
 
5.4%
Hangul
ValueCountFrequency (%)
로 173
 
8.0%
종 162
 
7.5%
서 145
 
6.7%
시 141
 
6.6%
구 141
 
6.6%
특 140
 
6.5%
별 140
 
6.5%
울 140
 
6.5%
동 115
 
5.3%
지 104
 
4.8%
Other values (160) 749
34.8%

도로명주소
Text

MISSING 

Distinct134
Distinct (%)97.1%
Missing2
Missing (%)1.4%
Memory size1.2 KiB
2024-05-11T00:36:47.428071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length42
Mean length30.898551
Min length21

Characters and Unicode

Total characters4264
Distinct characters191
Distinct categories10 ?
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 (%)94.9%

Sample

1st row서울특별시 종로구 종로66가길 6 (숭인동)
2nd row서울특별시 종로구 종로41길 48 (종로6가)
3rd row서울특별시 종로구 동호로 406-2 (종로5가)
4th row서울특별시 종로구 종로44길 82 (창신동)
5th row서울특별시 종로구 종로 252-6 (종로5가)
ValueCountFrequency (%)
서울특별시 138
 
16.2%
종로구 138
 
16.2%
지하1층 18
 
2.1%
종로 17
 
2.0%
3층 11
 
1.3%
내수동 11
 
1.3%
숭인동 10
 
1.2%
사직로8길 8
 
0.9%
율곡로 8
 
0.9%
지하2층 8
 
0.9%
Other values (291) 484
56.9%
2024-05-11T00:36:48.989036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
732
 
17.2%
로 292
 
6.8%
종 183
 
4.3%
1 153
 
3.6%
서 142
 
3.3%
시 141
 
3.3%
구 139
 
3.3%
( 138
 
3.2%
특 138
 
3.2%
별 138
 
3.2%
Other values (181) 2068
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2527
59.3%
Space Separator 732
 
17.2%
Decimal Number 586
 
13.7%
Open Punctuation 138
 
3.2%
Close Punctuation 138
 
3.2%
Other Punctuation 113
 
2.7%
Dash Punctuation 14
 
0.3%
Uppercase Letter 7
 
0.2%
Lowercase Letter 6
 
0.1%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 292
 
11.6%
종 183
 
7.2%
서 142
 
5.6%
시 141
 
5.6%
구 139
 
5.5%
특 138
 
5.5%
별 138
 
5.5%
울 138
 
5.5%
동 119
 
4.7%
층 71
 
2.8%
Other values (159) 1026
40.6%
Decimal Number
ValueCountFrequency (%)
1 153
26.1%
2 95
16.2%
3 64
10.9%
4 59
 
10.1%
0 49
 
8.4%
5 44
 
7.5%
8 40
 
6.8%
6 29
 
4.9%
9 27
 
4.6%
7 26
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
b 2
33.3%
w 1
16.7%
e 1
16.7%
s 1
16.7%
t 1
16.7%
Space Separator
ValueCountFrequency (%)
732
100.0%
Open Punctuation
ValueCountFrequency (%)
( 138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 138
100.0%
Other Punctuation
ValueCountFrequency (%)
, 113
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2527
59.3%
Common 1724
40.4%
Latin 13
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 292
 
11.6%
종 183
 
7.2%
서 142
 
5.6%
시 141
 
5.6%
구 139
 
5.5%
특 138
 
5.5%
별 138
 
5.5%
울 138
 
5.5%
동 119
 
4.7%
층 71
 
2.8%
Other values (159) 1026
40.6%
Common
ValueCountFrequency (%)
732
42.5%
1 153
 
8.9%
( 138
 
8.0%
) 138
 
8.0%
, 113
 
6.6%
2 95
 
5.5%
3 64
 
3.7%
4 59
 
3.4%
0 49
 
2.8%
5 44
 
2.6%
Other values (6) 139
 
8.1%
Latin
ValueCountFrequency (%)
B 7
53.8%
b 2
 
15.4%
w 1
 
7.7%
e 1
 
7.7%
s 1
 
7.7%
t 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2527
59.3%
ASCII 1737
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
732
42.1%
1 153
 
8.8%
( 138
 
7.9%
) 138
 
7.9%
, 113
 
6.5%
2 95
 
5.5%
3 64
 
3.7%
4 59
 
3.4%
0 49
 
2.8%
5 44
 
2.5%
Other values (12) 152
 
8.8%
Hangul
ValueCountFrequency (%)
로 292
 
11.6%
종 183
 
7.2%
서 142
 
5.6%
시 141
 
5.6%
구 139
 
5.5%
특 138
 
5.5%
별 138
 
5.5%
울 138
 
5.5%
동 119
 
4.7%
층 71
 
2.8%
Other values (159) 1026
40.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)63.9%
Missing32
Missing (%)22.9%
Infinite0
Infinite (%)0.0%
Mean5113
Minimum3008
Maximum110846
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T00:36:49.498145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3008
5-th percentile3011.35
Q13073.75
median3127
Q33174.25
95-th percentile3193.95
Maximum110846
Range107838
Interquartile range (IQR)100.5

Descriptive statistics

Standard deviation14585.032
Coefficient of variation (CV)2.852539
Kurtosis51.422167
Mean5113
Median Absolute Deviation (MAD)49.5
Skewness7.2435561
Sum552204
Variance2.1272316 × 108
MonotonicityNot monotonic
2024-05-11T00:36:49.992150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3174 6
 
4.3%
3041 4
 
2.9%
3173 4
 
2.9%
3189 4
 
2.9%
3157 3
 
2.1%
3009 3
 
2.1%
3114 3
 
2.1%
3127 3
 
2.1%
3175 3
 
2.1%
3182 3
 
2.1%
Other values (59) 72
51.4%
(Missing) 32
22.9%
ValueCountFrequency (%)
3008 1
 
0.7%
3009 3
2.1%
3010 1
 
0.7%
3011 1
 
0.7%
3012 1
 
0.7%
3013 1
 
0.7%
3019 1
 
0.7%
3021 1
 
0.7%
3025 1
 
0.7%
3030 1
 
0.7%
ValueCountFrequency (%)
110846 1
 
0.7%
110754 1
 
0.7%
3197 1
 
0.7%
3196 2
1.4%
3195 1
 
0.7%
3192 2
1.4%
3190 2
1.4%
3189 4
2.9%
3188 1
 
0.7%
3185 1
 
0.7%

사업장명
Text

Distinct136
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T00:36:50.612868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length17
Mean length7.7
Min length2

Characters and Unicode

Total characters1078
Distinct characters267
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

Unique133 ?
Unique (%)95.0%

Sample

1st row종로헬스
2nd row우진헬스
3rd row로타리헬스
4th row청송헬스
5th row용림헬스
ValueCountFrequency (%)
휘트니스 7
 
3.5%
피트니스 5
 
2.5%
gym 4
 
2.0%
종로헬스 3
 
1.5%
pt 3
 
1.5%
혜화점 2
 
1.0%
광화문역점 2
 
1.0%
스포애니 2
 
1.0%
짐 2
 
1.0%
은석스포츠센타 2
 
1.0%
Other values (167) 168
84.0%
2024-05-11T00:36:51.567180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 101
 
9.4%
60
 
5.6%
트 38
 
3.5%
니 33
 
3.1%
헬 25
 
2.3%
휘 21
 
1.9%
이 20
 
1.9%
T 19
 
1.8%
짐 19
 
1.8%
포 19
 
1.8%
Other values (257) 723
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 832
77.2%
Uppercase Letter 107
 
9.9%
Space Separator 60
 
5.6%
Close Punctuation 18
 
1.7%
Lowercase Letter 18
 
1.7%
Open Punctuation 17
 
1.6%
Other Punctuation 13
 
1.2%
Decimal Number 11
 
1.0%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 101
 
12.1%
트 38
 
4.6%
니 33
 
4.0%
헬 25
 
3.0%
휘 21
 
2.5%
이 20
 
2.4%
짐 19
 
2.3%
포 19
 
2.3%
로 18
 
2.2%
피 16
 
1.9%
Other values (208) 522
62.7%
Uppercase Letter
ValueCountFrequency (%)
T 19
17.8%
P 11
10.3%
M 10
 
9.3%
G 9
 
8.4%
A 7
 
6.5%
N 6
 
5.6%
Y 6
 
5.6%
O 5
 
4.7%
I 5
 
4.7%
D 4
 
3.7%
Other values (13) 25
23.4%
Lowercase Letter
ValueCountFrequency (%)
e 4
22.2%
s 3
16.7%
o 2
11.1%
l 2
11.1%
n 1
 
5.6%
y 1
 
5.6%
c 1
 
5.6%
m 1
 
5.6%
i 1
 
5.6%
t 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 4
36.4%
0 2
18.2%
4 1
 
9.1%
5 1
 
9.1%
2 1
 
9.1%
3 1
 
9.1%
7 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 5
38.5%
& 5
38.5%
, 2
 
15.4%
? 1
 
7.7%
Space Separator
ValueCountFrequency (%)
60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 832
77.2%
Latin 125
 
11.6%
Common 121
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 101
 
12.1%
트 38
 
4.6%
니 33
 
4.0%
헬 25
 
3.0%
휘 21
 
2.5%
이 20
 
2.4%
짐 19
 
2.3%
포 19
 
2.3%
로 18
 
2.2%
피 16
 
1.9%
Other values (208) 522
62.7%
Latin
ValueCountFrequency (%)
T 19
15.2%
P 11
 
8.8%
M 10
 
8.0%
G 9
 
7.2%
A 7
 
5.6%
N 6
 
4.8%
Y 6
 
4.8%
O 5
 
4.0%
I 5
 
4.0%
D 4
 
3.2%
Other values (24) 43
34.4%
Common
ValueCountFrequency (%)
60
49.6%
) 18
 
14.9%
( 17
 
14.0%
. 5
 
4.1%
& 5
 
4.1%
1 4
 
3.3%
- 2
 
1.7%
0 2
 
1.7%
, 2
 
1.7%
4 1
 
0.8%
Other values (5) 5
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 832
77.2%
ASCII 246
 
22.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 101
 
12.1%
트 38
 
4.6%
니 33
 
4.0%
헬 25
 
3.0%
휘 21
 
2.5%
이 20
 
2.4%
짐 19
 
2.3%
포 19
 
2.3%
로 18
 
2.2%
피 16
 
1.9%
Other values (208) 522
62.7%
ASCII
ValueCountFrequency (%)
60
24.4%
T 19
 
7.7%
) 18
 
7.3%
( 17
 
6.9%
P 11
 
4.5%
M 10
 
4.1%
G 9
 
3.7%
A 7
 
2.8%
N 6
 
2.4%
Y 6
 
2.4%
Other values (39) 83
33.7%

최종수정일자
Date

Distinct134
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2003-02-07 09:11:15
Maximum2024-04-29 17:48:49
2024-05-11T00:36:51.967028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:36:52.708343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
I
72 
U
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowU
3rd rowU
4th rowI
5th rowU

Common Values

ValueCountFrequency (%)
I 72
51.4%
U 68
48.6%

Length

2024-05-11T00:36:53.142800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:36:53.493668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 72
51.4%
u 68
48.6%

데이터갱신일자
Date

Distinct65
Distinct (%)46.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:01:00
2024-05-11T00:36:53.834080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:36:54.267931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct117
Distinct (%)84.8%
Missing2
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean198752.65
Minimum196143.26
Maximum201963.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T00:36:54.810843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196143.26
5-th percentile196618.62
Q1197454.98
median198541.72
Q3199993.51
95-th percentile201350.47
Maximum201963.94
Range5820.6826
Interquartile range (IQR)2538.5252

Descriptive statistics

Standard deviation1508.6172
Coefficient of variation (CV)0.0075904256
Kurtosis-0.96791197
Mean198752.65
Median Absolute Deviation (MAD)1220.0331
Skewness0.35023323
Sum27427866
Variance2275925.9
MonotonicityNot monotonic
2024-05-11T00:36:55.281210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197329.898847331 5
 
3.6%
201350.473375538 3
 
2.1%
197212.364862058 3
 
2.1%
197725.951068718 3
 
2.1%
200003.902251234 3
 
2.1%
198150.300374121 3
 
2.1%
199812.609633255 2
 
1.4%
199976.765493088 2
 
1.4%
197680.780080175 2
 
1.4%
197567.93800572 2
 
1.4%
Other values (107) 110
78.6%
ValueCountFrequency (%)
196143.256118357 1
0.7%
196248.34462033 1
0.7%
196428.478415698 1
0.7%
196467.975088253 1
0.7%
196496.681277096 2
1.4%
196560.829310338 1
0.7%
196628.815833341 1
0.7%
196693.13596032 1
0.7%
196801.190594539 1
0.7%
196810.084509451 1
0.7%
ValueCountFrequency (%)
201963.938724209 1
 
0.7%
201946.86632604 1
 
0.7%
201837.706250201 1
 
0.7%
201798.834918812 1
 
0.7%
201702.974433451 1
 
0.7%
201359.53353905 1
 
0.7%
201350.473375538 3
2.1%
201341.677424554 1
 
0.7%
201258.062657124 1
 
0.7%
201237.98437273 1
 
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct117
Distinct (%)84.8%
Missing2
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean452764.08
Minimum451664.4
Maximum456251.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T00:36:55.803929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451664.4
5-th percentile451884.82
Q1452045.46
median452406.13
Q3452850.28
95-th percentile456041.73
Maximum456251.74
Range4587.3412
Interquartile range (IQR)804.81999

Descriptive statistics

Standard deviation1126.0926
Coefficient of variation (CV)0.0024871509
Kurtosis3.4228689
Mean452764.08
Median Absolute Deviation (MAD)367.34037
Skewness2.0384924
Sum62481443
Variance1268084.6
MonotonicityNot monotonic
2024-05-11T00:36:56.301284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452432.501606302 5
 
3.6%
452279.7442603 3
 
2.1%
456055.205802855 3
 
2.1%
456251.740629682 3
 
2.1%
452556.060739615 3
 
2.1%
452019.212642931 3
 
2.1%
452132.648343993 2
 
1.4%
452526.527263312 2
 
1.4%
452016.543891352 2
 
1.4%
452276.454633376 2
 
1.4%
Other values (107) 110
78.6%
ValueCountFrequency (%)
451664.399383222 1
0.7%
451786.479083595 1
0.7%
451789.694049663 1
0.7%
451797.477709718 1
0.7%
451842.501561085 1
0.7%
451848.180035467 1
0.7%
451869.596952219 1
0.7%
451887.51214766 1
0.7%
451889.198243161 1
0.7%
451891.299622979 1
0.7%
ValueCountFrequency (%)
456251.740629682 3
2.1%
456082.500270084 1
 
0.7%
456055.205802855 3
2.1%
456039.354846116 1
 
0.7%
455959.269196762 1
 
0.7%
455911.163224671 1
 
0.7%
455671.010197127 1
 
0.7%
455057.030366286 1
 
0.7%
454257.479097309 1
 
0.7%
453951.931931301 1
 
0.7%

문화체육업종명
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
체력단련장업
93 
<NA>
47 

Length

Max length6
Median length6
Mean length5.3285714
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 93
66.4%
<NA> 47
33.6%

Length

2024-05-11T00:36:56.855813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:36:57.375032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 93
66.4%
na 47
33.6%

공사립구분명
Categorical

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
사립
91 
<NA>
47 
공립
 
2

Length

Max length4
Median length2
Mean length2.6714286
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 91
65.0%
<NA> 47
33.6%
공립 2
 
1.4%

Length

2024-05-11T00:36:57.808296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:36:58.239569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 91
65.0%
na 47
33.6%
공립 2
 
1.4%

보험가입여부코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
129 
0
 
11

Length

Max length4
Median length4
Mean length3.7642857
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> 129
92.1%
0 11
 
7.9%

Length

2024-05-11T00:36:58.815002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:36:59.297447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 129
92.1%
0 11
 
7.9%

지도자수
Categorical

Distinct5
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
99 
1
24 
0
 
9
2
 
6
3
 
2

Length

Max length4
Median length4
Mean length3.1214286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 99
70.7%
1 24
 
17.1%
0 9
 
6.4%
2 6
 
4.3%
3 2
 
1.4%

Length

2024-05-11T00:36:59.829550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:37:00.264886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 99
70.7%
1 24
 
17.1%
0 9
 
6.4%
2 6
 
4.3%
3 2
 
1.4%

건축물동수
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
112 
0
27 
1
 
1

Length

Max length4
Median length4
Mean length3.4
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 112
80.0%
0 27
 
19.3%
1 1
 
0.7%

Length

2024-05-11T00:37:00.806707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:37:01.198413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 112
80.0%
0 27
 
19.3%
1 1
 
0.7%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)51.0%
Missing91
Missing (%)65.0%
Infinite0
Infinite (%)0.0%
Mean9807.8229
Minimum0
Maximum135170.79
Zeros25
Zeros (%)17.9%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T00:37:01.711342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32861.31
95-th percentile58019.308
Maximum135170.79
Range135170.79
Interquartile range (IQR)2861.31

Descriptive statistics

Standard deviation25372.46
Coefficient of variation (CV)2.5869615
Kurtosis14.002497
Mean9807.8229
Median Absolute Deviation (MAD)0
Skewness3.5958604
Sum480583.32
Variance6.4376174 × 108
MonotonicityNot monotonic
2024-05-11T00:37:02.193280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.0 25
 
17.9%
762.06 1
 
0.7%
1120.84 1
 
0.7%
598.87 1
 
0.7%
732.18 1
 
0.7%
135170.79 1
 
0.7%
1404.2 1
 
0.7%
19412.5 1
 
0.7%
69290.02 1
 
0.7%
2077.65 1
 
0.7%
Other values (15) 15
 
10.7%
(Missing) 91
65.0%
ValueCountFrequency (%)
0.0 25
17.9%
549.01 1
 
0.7%
598.87 1
 
0.7%
676.68 1
 
0.7%
690.48 1
 
0.7%
732.18 1
 
0.7%
762.06 1
 
0.7%
789.98 1
 
0.7%
1120.84 1
 
0.7%
1404.2 1
 
0.7%
ValueCountFrequency (%)
135170.79 1
0.7%
89808.14 1
0.7%
69290.02 1
0.7%
41113.24 1
0.7%
28115.26 1
0.7%
23255.71 1
0.7%
22413.21 1
0.7%
20698.73 1
0.7%
19412.5 1
0.7%
9936.0 1
0.7%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
137 
0
 
3

Length

Max length4
Median length4
Mean length3.9357143
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> 137
97.9%
0 3
 
2.1%

Length

2024-05-11T00:37:02.811724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:37:03.208868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 137
97.9%
0 3
 
2.1%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03000000CDFH330106198900000119891230<NA>3폐업3폐업19980907<NA><NA><NA><NA><NA>110825서울특별시 종로구 숭인동 201-5번지서울특별시 종로구 종로66가길 6 (숭인동)<NA>종로헬스2003-02-07 09:11:15I2018-08-31 23:59:59.0<NA>201837.70625452386.077965체력단련장업사립<NA>000.0<NA><NA><NA>
13000000CDFH330106198900000219891230<NA>3폐업3폐업20181001<NA><NA><NA>02-765-4738<NA><NA>서울특별시 종로구 종로6가 210-11번지서울특별시 종로구 종로41길 48 (종로6가)3124우진헬스2018-10-22 15:11:50U2018-10-24 02:37:18.0<NA>200492.343926452341.395311체력단련장업사립<NA><NA><NA><NA><NA><NA><NA>
23000000CDFH330106199000000119901124<NA>3폐업3폐업20181001<NA><NA><NA><NA><NA>110836서울특별시 종로구 종로5가 182-6번지서울특별시 종로구 동호로 406-2 (종로5가)3196로타리헬스2018-10-22 15:10:55U2018-10-24 02:37:18.0<NA>200143.159226452039.535286체력단련장업사립<NA><NA>00.0<NA><NA><NA>
33000000CDFH330106199200000119920609<NA>3폐업3폐업20140210<NA><NA><NA>02-763-7715<NA>110841서울특별시 종로구 창신동 407-4번지서울특별시 종로구 종로44길 82 (창신동)<NA>청송헬스2014-08-26 20:44:16I2018-08-31 23:59:59.0<NA>201237.984373452042.140095체력단련장업사립<NA><NA>00.0<NA><NA><NA>
43000000CDFH330106199200000219920716<NA>3폐업3폐업20200220<NA><NA><NA><NA><NA><NA>서울특별시 종로구 종로5가 265-12번지서울특별시 종로구 종로 252-6 (종로5가)3197용림헬스2020-02-21 09:30:44U2020-02-23 02:40:00.0<NA>200434.095062452049.068623체력단련장업사립<NA><NA>00.0<NA><NA><NA>
53000000CDFH330106199300000119930702<NA>3폐업3폐업20140102<NA><NA><NA>02-743-4016<NA>110470서울특별시 종로구 연지동 170번지서울특별시 종로구 종로31길 54 (연지동)<NA>우진체육관2014-08-26 20:42:51I2018-08-31 23:59:59.0<NA>199821.768264452316.953823체력단련장업사립<NA><NA>00.0<NA><NA><NA>
63000000CDFH330106199300000219930813<NA>3폐업3폐업20030325<NA><NA><NA><NA><NA>110090서울특별시 종로구 교북동 10-10번지서울특별시 종로구 통일로 206 (교북동)<NA>승리헬스2003-03-25 15:03:50I2018-08-31 23:59:59.0<NA>196496.681277452158.479696체력단련장업사립0<NA><NA><NA><NA><NA><NA>
73000000CDFH330106199400000119940516<NA>3폐업3폐업20000418<NA><NA><NA><NA><NA>110121서울특별시 종로구 종로1가 21번지<NA><NA>개선헬스2003-02-07 09:11:15I2018-08-31 23:59:59.0<NA><NA><NA>체력단련장업사립<NA>000.0<NA><NA><NA>
83000000CDFH330106199400000219940616<NA>3폐업3폐업20181001<NA><NA><NA>02-742-7953<NA><NA>서울특별시 종로구 효제동 247-3번지서울특별시 종로구 대학로2길 3 (효제동)3126청우헬스2018-10-22 15:03:52U2018-10-24 02:37:18.0<NA>200132.956151452141.120208체력단련장업사립<NA><NA>00.0<NA><NA><NA>
93000000CDFH330106199500000119950224<NA>3폐업3폐업20181001<NA><NA><NA>02-2274-0798<NA><NA>서울특별시 종로구 종로5가 138-2번지서울특별시 종로구 종로 214 (종로5가)3195종로헬스2018-10-22 15:04:22U2018-10-24 02:37:18.0<NA>200067.053022452046.218596체력단련장업사립<NA><NA>00.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
1303000000CDFH33010620230000052023-08-17<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 무악동 63-10서울특별시 종로구 통일로16길 5, 지하2층 (무악동)3030더 루트짐2023-08-17 10:19:27I2022-12-07 23:09:00.0<NA>196143.256118452619.543629<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1313000000CDFH33010620230000062023-08-31<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 명륜1가 83-5 새주빌딩서울특별시 종로구 성균관로 40, 새주빌딩 지하1층 (명륜1가)3069어메이징휘트니스 혜화점2023-08-31 10:34:24I2022-12-09 00:02:00.0<NA>199658.555068453782.816291<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1323000000CDFH33010620230000072023-10-05<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 창신동 540-1 대산 빌딩서울특별시 종로구 종로 305-2, 대산 빌딩 4층 (창신동)3106짱핏2023-10-05 14:55:13I2022-10-31 00:07:00.0<NA>200968.658983452212.51928<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1333000000CDFH33010620230000082023-10-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 세종로 202-1서울특별시 종로구 세종대로 159, 11층 (세종로)3183Dooice Gym2023-10-19 10:05:49I2022-10-30 22:01:00.0<NA>197841.421685452035.17683<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1343000000CDFH33010620230000092023-10-31<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 평창동 331 쇼핑센타뉴본서울특별시 종로구 평창11길 3, 쇼핑센타뉴본 3층 (평창동)3008애플 피트니스2023-11-16 14:16:34U2022-10-31 23:08:00.0<NA>196965.164175455959.269197<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1353000000CDFH33010620230000102023-11-24<NA>1영업/정상13영업중<NA><NA><NA><NA>1661-0835<NA><NA>서울특별시 종로구 내자동 19 사학회관서울특별시 종로구 사직로 113, 사학회관 지하2층 (내자동)3041종로청운스포렉스 피트니스센터2024-04-29 17:48:49U2023-12-05 00:01:00.0<NA>197397.284209452669.835426<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1363000000CDFH33010620230000112023-12-06<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 숭인동 81-15 필빌딩서울특별시 종로구 지봉로 50, 필빌딩 지하1층 (숭인동)3113온리스?짐2024-03-21 17:19:32U2023-12-02 22:03:00.0<NA>201341.677425452471.587515<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1373000000CDFH33010620240000012024-01-31<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 신영동 72-10 고석빌딩서울특별시 종로구 평창문화로 6-3, 고석빌딩 1층 (신영동)3019바름체형교정재활&키성장운동센터 디스크,무릎통증전문 종로점2024-02-02 08:16:10U2023-12-02 00:04:00.0<NA>196628.815833455671.010197<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1383000000CDFH33010620240000022024-02-15<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 내수동 4 옥빌딩서울특별시 종로구 새문안로5가길 11, 옥빌딩 202호 (내수동)3173베이지 피트니스2024-02-15 13:38:20I2023-12-01 23:07:00.0<NA>197618.459741452311.285166<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1393000000CDFH33010620240000032024-04-05<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 신문로1가 25 정우빌딩서울특별시 종로구 새문안로 89, 정우빌딩 지하1층 (신문로1가)3182크로스핏엠비션 광화문역점2024-04-05 13:17:42I2023-12-04 00:07:00.0<NA>197680.78008452016.543891<NA><NA><NA><NA><NA><NA><NA><NA><NA>