Overview

Dataset statistics

Number of variables21
Number of observations80
Missing cells428
Missing cells (%)25.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.0 KiB
Average record size in memory179.7 B

Variable types

Categorical8
Text4
DateTime2
Unsupported3
Numeric3
Boolean1

Alerts

문화체육업종명 has constant value ""Constant
공사립구분명 has constant value ""Constant
보험가입여부코드 has constant value ""Constant
영업상태구분코드 is highly imbalanced (83.3%)Imbalance
도로명우편번호 is highly imbalanced (85.5%)Imbalance
X좌표값 is highly imbalanced (85.5%)Imbalance
Y좌표값 is highly imbalanced (85.5%)Imbalance
인허가취소일자 has 80 (100.0%) missing valuesMissing
폐업일자 has 27 (33.8%) missing valuesMissing
소재지시설전화번호 has 78 (97.5%) missing valuesMissing
소재지면적정보 has 80 (100.0%) missing valuesMissing
소재지도로명주소 has 1 (1.2%) missing valuesMissing
소재지우편번호 has 1 (1.2%) missing valuesMissing
WGS84위도 has 1 (1.2%) missing valuesMissing
WGS84경도 has 1 (1.2%) missing valuesMissing
업태구분명정보 has 80 (100.0%) missing valuesMissing
보험가입여부코드 has 79 (98.8%) missing valuesMissing
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 21:21:15.235133
Analysis finished2023-12-10 21:21:15.573806
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct20
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
안양시
14 
의정부시
12 
광명시
11 
안산시
6 
군포시
5 
Other values (15)
32 

Length

Max length4
Median length3
Mean length3.175
Min length3

Unique

Unique7 ?
Unique (%)8.8%

Sample

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

Common Values

ValueCountFrequency (%)
안양시 14
17.5%
의정부시 12
15.0%
광명시 11
13.8%
안산시 6
7.5%
군포시 5
 
6.2%
부천시 5
 
6.2%
성남시 4
 
5.0%
고양시 3
 
3.8%
수원시 3
 
3.8%
이천시 3
 
3.8%
Other values (10) 14
17.5%

Length

2023-12-11T06:21:15.632118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안양시 14
17.5%
의정부시 12
15.0%
광명시 11
13.8%
안산시 6
7.5%
군포시 5
 
6.2%
부천시 5
 
6.2%
성남시 4
 
5.0%
이천시 3
 
3.8%
포천시 3
 
3.8%
수원시 3
 
3.8%
Other values (10) 14
17.5%

사업장명
Text

Distinct71
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-11T06:21:15.851417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length5
Mean length5.525
Min length1

Characters and Unicode

Total characters442
Distinct characters113
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)80.0%

Sample

1st row윙윙댄스스포츠
2nd row일산무도장
3rd row벽제
4th row동서 무도장
5th row광명 스포츠 아카데미
ValueCountFrequency (%)
무도장 10
 
10.1%
무도학원 6
 
6.1%
팡팡무도장 3
 
3.0%
중앙무도장 3
 
3.0%
역전무도장 2
 
2.0%
현대무도장 2
 
2.0%
진주무도장 2
 
2.0%
스타무도장 2
 
2.0%
광명 2
 
2.0%
가야무도장 2
 
2.0%
Other values (65) 65
65.7%
2023-12-11T06:21:16.218547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 72
16.3%
무 70
15.8%
장 69
 
15.6%
19
 
4.3%
원 8
 
1.8%
스 7
 
1.6%
학 6
 
1.4%
대 6
 
1.4%
팡 6
 
1.4%
명 5
 
1.1%
Other values (103) 174
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 420
95.0%
Space Separator 19
 
4.3%
Decimal Number 2
 
0.5%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 72
17.1%
무 70
16.7%
장 69
16.4%
원 8
 
1.9%
스 7
 
1.7%
학 6
 
1.4%
대 6
 
1.4%
팡 6
 
1.4%
명 5
 
1.2%
태 5
 
1.2%
Other values (99) 166
39.5%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 420
95.0%
Common 21
 
4.8%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 72
17.1%
무 70
16.7%
장 69
16.4%
원 8
 
1.9%
스 7
 
1.7%
학 6
 
1.4%
대 6
 
1.4%
팡 6
 
1.4%
명 5
 
1.2%
태 5
 
1.2%
Other values (99) 166
39.5%
Common
ValueCountFrequency (%)
19
90.5%
2 1
 
4.8%
1 1
 
4.8%
Latin
ValueCountFrequency (%)
J 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 420
95.0%
ASCII 22
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 72
17.1%
무 70
16.7%
장 69
16.4%
원 8
 
1.9%
스 7
 
1.7%
학 6
 
1.4%
대 6
 
1.4%
팡 6
 
1.4%
명 5
 
1.2%
태 5
 
1.2%
Other values (99) 166
39.5%
ASCII
ValueCountFrequency (%)
19
86.4%
2 1
 
4.5%
1 1
 
4.5%
J 1
 
4.5%

인허가일자
Date

Distinct68
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
Minimum1996-06-05 00:00:00
Maximum2020-11-24 00:00:00
2023-12-11T06:21:16.350619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:21:16.519076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing80
Missing (%)100.0%
Memory size852.0 B

영업상태구분코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size772.0 B
<NA>
77 
13
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.9125
Min length1

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 77
96.2%
13 2
 
2.5%
3 1
 
1.2%

Length

2023-12-11T06:21:16.664226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:21:16.756583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 77
96.2%
13 2
 
2.5%
3 1
 
1.2%

영업상태명
Categorical

Distinct4
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
폐업 등
52 
운영중
25 
영업중
 
2
폐업
 
1

Length

Max length4
Median length4
Mean length3.6375
Min length2

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 등 52
65.0%
운영중 25
31.2%
영업중 2
 
2.5%
폐업 1
 
1.2%

Length

2023-12-11T06:21:16.865861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:21:16.975999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 53
40.2%
등 52
39.4%
운영중 25
18.9%
영업중 2
 
1.5%

폐업일자
Date

MISSING 

Distinct50
Distinct (%)94.3%
Missing27
Missing (%)33.8%
Memory size772.0 B
Minimum1999-11-12 00:00:00
Maximum2023-05-17 00:00:00
2023-12-11T06:21:17.077125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:21:17.207141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지시설전화번호
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing78
Missing (%)97.5%
Memory size772.0 B
2023-12-11T06:21:17.374923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters24
Distinct characters10
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

Unique2 ?
Unique (%)100.0%

Sample

1st row031-868-2541
2nd row031-484-7080
ValueCountFrequency (%)
031-868-2541 1
50.0%
031-484-7080 1
50.0%
2023-12-11T06:21:17.603322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4
16.7%
- 4
16.7%
8 4
16.7%
1 3
12.5%
4 3
12.5%
3 2
8.3%
6 1
 
4.2%
2 1
 
4.2%
5 1
 
4.2%
7 1
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20
83.3%
Dash Punctuation 4
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4
20.0%
8 4
20.0%
1 3
15.0%
4 3
15.0%
3 2
10.0%
6 1
 
5.0%
2 1
 
5.0%
5 1
 
5.0%
7 1
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4
16.7%
- 4
16.7%
8 4
16.7%
1 3
12.5%
4 3
12.5%
3 2
8.3%
6 1
 
4.2%
2 1
 
4.2%
5 1
 
4.2%
7 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4
16.7%
- 4
16.7%
8 4
16.7%
1 3
12.5%
4 3
12.5%
3 2
8.3%
6 1
 
4.2%
2 1
 
4.2%
5 1
 
4.2%
7 1
 
4.2%

소재지면적정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing80
Missing (%)100.0%
Memory size852.0 B

도로명우편번호
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
<NA>
77 
11334
 
1
15361
 
1
13951
 
1

Length

Max length5
Median length4
Mean length4.0375
Min length4

Unique

Unique3 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 77
96.2%
11334 1
 
1.2%
15361 1
 
1.2%
13951 1
 
1.2%

Length

2023-12-11T06:21:17.716543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:21:17.806475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 77
96.2%
11334 1
 
1.2%
15361 1
 
1.2%
13951 1
 
1.2%

소재지도로명주소
Text

MISSING 

Distinct77
Distinct (%)97.5%
Missing1
Missing (%)1.2%
Memory size772.0 B
2023-12-11T06:21:18.037887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length42
Mean length31.43038
Min length15

Characters and Unicode

Total characters2483
Distinct characters160
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

Unique75 ?
Unique (%)94.9%

Sample

1st row경기도 고양시 일산동구 중앙로1261번길 19, 1001호 (장항동, 호수광장빌딩)
2nd row경기도 고양시 일산서구 고양대로632번길 74, 2층 (일산동, 제일빌딩)
3rd row경기도 고양시 덕양구 통일로768번길 12-7 (관산동)
4th row경기도 광명시 광명로 910 (광명동)
5th row경기도 광명시 오리로985번길 4 (광명동)
ValueCountFrequency (%)
경기도 79
 
16.3%
안양시 14
 
2.9%
의정부시 12
 
2.5%
광명시 11
 
2.3%
의정부동 10
 
2.1%
만안구 8
 
1.6%
광명동 6
 
1.2%
동안구 6
 
1.2%
안산시 6
 
1.2%
단원구 6
 
1.2%
Other values (245) 328
67.5%
2023-12-11T06:21:18.422877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
445
 
17.9%
시 85
 
3.4%
동 84
 
3.4%
경 83
 
3.3%
기 82
 
3.3%
도 79
 
3.2%
로 77
 
3.1%
, 77
 
3.1%
1 76
 
3.1%
) 76
 
3.1%
Other values (150) 1319
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1363
54.9%
Space Separator 445
 
17.9%
Decimal Number 416
 
16.8%
Other Punctuation 77
 
3.1%
Close Punctuation 76
 
3.1%
Open Punctuation 76
 
3.1%
Uppercase Letter 14
 
0.6%
Dash Punctuation 10
 
0.4%
Math Symbol 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 85
 
6.2%
동 84
 
6.2%
경 83
 
6.1%
기 82
 
6.0%
도 79
 
5.8%
로 77
 
5.6%
안 50
 
3.7%
길 37
 
2.7%
양 36
 
2.6%
번 35
 
2.6%
Other values (130) 715
52.5%
Decimal Number
ValueCountFrequency (%)
1 76
18.3%
2 59
14.2%
0 53
12.7%
3 51
12.3%
4 42
10.1%
6 32
7.7%
8 32
7.7%
5 31
7.5%
7 21
 
5.0%
9 19
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 11
78.6%
A 1
 
7.1%
P 1
 
7.1%
T 1
 
7.1%
Space Separator
ValueCountFrequency (%)
445
100.0%
Other Punctuation
ValueCountFrequency (%)
, 77
100.0%
Close Punctuation
ValueCountFrequency (%)
) 76
100.0%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1363
54.9%
Common 1106
44.5%
Latin 14
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 85
 
6.2%
동 84
 
6.2%
경 83
 
6.1%
기 82
 
6.0%
도 79
 
5.8%
로 77
 
5.6%
안 50
 
3.7%
길 37
 
2.7%
양 36
 
2.6%
번 35
 
2.6%
Other values (130) 715
52.5%
Common
ValueCountFrequency (%)
445
40.2%
, 77
 
7.0%
1 76
 
6.9%
) 76
 
6.9%
( 76
 
6.9%
2 59
 
5.3%
0 53
 
4.8%
3 51
 
4.6%
4 42
 
3.8%
6 32
 
2.9%
Other values (6) 119
 
10.8%
Latin
ValueCountFrequency (%)
B 11
78.6%
A 1
 
7.1%
P 1
 
7.1%
T 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1363
54.9%
ASCII 1120
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
445
39.7%
, 77
 
6.9%
1 76
 
6.8%
) 76
 
6.8%
( 76
 
6.8%
2 59
 
5.3%
0 53
 
4.7%
3 51
 
4.6%
4 42
 
3.8%
6 32
 
2.9%
Other values (10) 133
 
11.9%
Hangul
ValueCountFrequency (%)
시 85
 
6.2%
동 84
 
6.2%
경 83
 
6.1%
기 82
 
6.0%
도 79
 
5.8%
로 77
 
5.6%
안 50
 
3.7%
길 37
 
2.7%
양 36
 
2.6%
번 35
 
2.6%
Other values (130) 715
52.5%

소재지지번주소
Text

Distinct78
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-11T06:21:18.685315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length36
Mean length26.975
Min length15

Characters and Unicode

Total characters2158
Distinct characters136
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

Unique76 ?
Unique (%)95.0%

Sample

1st row경기도 고양시 일산동구 장항동 857번지
2nd row경기도 고양시 일산서구 일산동 655-8번지 2층 일부
3rd row경기도 고양시 덕양구 관산동 179-2번지
4th row경기도 광명시 광명동 158-79번지 3층
5th row경기도 광명시 광명동 158-811번지
ValueCountFrequency (%)
경기도 80
 
17.9%
안양시 14
 
3.1%
의정부동 12
 
2.7%
의정부시 12
 
2.7%
광명시 11
 
2.5%
3층 10
 
2.2%
지하1층 8
 
1.8%
만안구 8
 
1.8%
안양동 8
 
1.8%
광명동 7
 
1.6%
Other values (202) 278
62.1%
2023-12-11T06:21:19.100537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
371
 
17.2%
지 99
 
4.6%
1 95
 
4.4%
동 87
 
4.0%
시 82
 
3.8%
기 81
 
3.8%
경 80
 
3.7%
도 80
 
3.7%
번 77
 
3.6%
- 69
 
3.2%
Other values (126) 1037
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1217
56.4%
Decimal Number 463
 
21.5%
Space Separator 371
 
17.2%
Dash Punctuation 69
 
3.2%
Other Punctuation 16
 
0.7%
Uppercase Letter 15
 
0.7%
Math Symbol 5
 
0.2%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 99
 
8.1%
동 87
 
7.1%
시 82
 
6.7%
기 81
 
6.7%
경 80
 
6.6%
도 80
 
6.6%
번 77
 
6.3%
안 43
 
3.5%
층 40
 
3.3%
부 33
 
2.7%
Other values (106) 515
42.3%
Decimal Number
ValueCountFrequency (%)
1 95
20.5%
2 58
12.5%
3 54
11.7%
5 51
11.0%
4 44
9.5%
6 38
 
8.2%
0 38
 
8.2%
8 30
 
6.5%
9 28
 
6.0%
7 27
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
B 12
80.0%
A 1
 
6.7%
P 1
 
6.7%
T 1
 
6.7%
Space Separator
ValueCountFrequency (%)
371
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1217
56.4%
Common 926
42.9%
Latin 15
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 99
 
8.1%
동 87
 
7.1%
시 82
 
6.7%
기 81
 
6.7%
경 80
 
6.6%
도 80
 
6.6%
번 77
 
6.3%
안 43
 
3.5%
층 40
 
3.3%
부 33
 
2.7%
Other values (106) 515
42.3%
Common
ValueCountFrequency (%)
371
40.1%
1 95
 
10.3%
- 69
 
7.5%
2 58
 
6.3%
3 54
 
5.8%
5 51
 
5.5%
4 44
 
4.8%
6 38
 
4.1%
0 38
 
4.1%
8 30
 
3.2%
Other values (6) 78
 
8.4%
Latin
ValueCountFrequency (%)
B 12
80.0%
A 1
 
6.7%
P 1
 
6.7%
T 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1217
56.4%
ASCII 941
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
371
39.4%
1 95
 
10.1%
- 69
 
7.3%
2 58
 
6.2%
3 54
 
5.7%
5 51
 
5.4%
4 44
 
4.7%
6 38
 
4.0%
0 38
 
4.0%
8 30
 
3.2%
Other values (10) 93
 
9.9%
Hangul
ValueCountFrequency (%)
지 99
 
8.1%
동 87
 
7.1%
시 82
 
6.7%
기 81
 
6.7%
경 80
 
6.6%
도 80
 
6.6%
번 77
 
6.3%
안 43
 
3.5%
층 40
 
3.3%
부 33
 
2.7%
Other values (106) 515
42.3%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct63
Distinct (%)79.7%
Missing1
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean350480.62
Minimum10402
Maximum487892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-11T06:21:19.467934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10402
5-th percentile11658.9
Q1414461.5
median425868
Q3453077
95-th percentile480848
Maximum487892
Range477490
Interquartile range (IQR)38615.5

Descriptive statistics

Standard deviation178802.41
Coefficient of variation (CV)0.51016348
Kurtosis-0.063684129
Mean350480.62
Median Absolute Deviation (MAD)16153
Skewness-1.3588569
Sum27687969
Variance3.1970303 × 1010
MonotonicityNot monotonic
2023-12-11T06:21:19.599252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
423807 4
 
5.0%
480842 3
 
3.8%
480840 2
 
2.5%
480841 2
 
2.5%
423837 2
 
2.5%
430833 2
 
2.5%
425868 2
 
2.5%
463828 2
 
2.5%
430826 2
 
2.5%
480848 2
 
2.5%
Other values (53) 56
70.0%
ValueCountFrequency (%)
10402 1
1.2%
11147 1
1.2%
11334 2
2.5%
11695 1
1.2%
11697 1
1.2%
11927 1
1.2%
12909 1
1.2%
13951 1
1.2%
14066 1
1.2%
15066 1
1.2%
ValueCountFrequency (%)
487892 1
 
1.2%
487040 1
 
1.2%
482812 1
 
1.2%
480848 2
2.5%
480843 1
 
1.2%
480842 3
3.8%
480841 2
2.5%
480840 2
2.5%
467804 1
 
1.2%
467800 1
 
1.2%

WGS84위도
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)92.4%
Missing1
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean37.508914
Minimum37.005882
Maximum38.091045
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-11T06:21:19.725285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.005882
5-th percentile37.28001
Q137.365994
median37.474879
Q337.706483
95-th percentile37.895521
Maximum38.091045
Range1.0851632
Interquartile range (IQR)0.3404895

Descriptive statistics

Standard deviation0.1994002
Coefficient of variation (CV)0.0053160751
Kurtosis0.0084952731
Mean37.508914
Median Absolute Deviation (MAD)0.12469707
Skewness0.59074801
Sum2963.2042
Variance0.039760442
MonotonicityNot monotonic
2023-12-11T06:21:19.848889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7394019398 2
 
2.5%
37.4024854516 2
 
2.5%
37.358108291 2
 
2.5%
37.7393101015 2
 
2.5%
37.3870579065 2
 
2.5%
37.9001975107 2
 
2.5%
37.4027756246 1
 
1.2%
37.7343040279 1
 
1.2%
37.236853065 1
 
1.2%
37.7244520439 1
 
1.2%
Other values (63) 63
78.8%
ValueCountFrequency (%)
37.0058819726 1
1.2%
37.236853065 1
1.2%
37.2775320766 1
1.2%
37.2778655739 1
1.2%
37.2802481042 1
1.2%
37.2807934689 1
1.2%
37.2810134854 1
1.2%
37.3171856552 1
1.2%
37.3174944509 1
1.2%
37.3185920522 1
1.2%
ValueCountFrequency (%)
38.0910451365 1
1.2%
37.9001975107 2
2.5%
37.8960965099 1
1.2%
37.8954575738 1
1.2%
37.8285712482 1
1.2%
37.7612560163 1
1.2%
37.7421294155 1
1.2%
37.741698121 1
1.2%
37.7406256146 1
1.2%
37.7394019398 2
2.5%

WGS84경도
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)92.4%
Missing1
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean126.97003
Minimum126.66508
Maximum127.44558
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-11T06:21:19.969675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.66508
5-th percentile126.77234
Q1126.85484
median126.93221
Q3127.05101
95-th percentile127.26812
Maximum127.44558
Range0.78050348
Interquartile range (IQR)0.19617638

Descriptive statistics

Standard deviation0.16154412
Coefficient of variation (CV)0.0012723012
Kurtosis1.1561801
Mean126.97003
Median Absolute Deviation (MAD)0.11185851
Skewness0.97624346
Sum10030.632
Variance0.026096502
MonotonicityNot monotonic
2023-12-11T06:21:20.131229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0501169382 2
 
2.5%
126.9754094942 2
 
2.5%
126.931939368 2
 
2.5%
127.0520355967 2
 
2.5%
126.9322064886 2
 
2.5%
127.0529389675 2
 
2.5%
126.9198290921 1
 
1.2%
127.0486951201 1
 
1.2%
127.2068978004 1
 
1.2%
126.9489315621 1
 
1.2%
Other values (63) 63
78.8%
ValueCountFrequency (%)
126.6650813107 1
1.2%
126.736841512 1
1.2%
126.7546226209 1
1.2%
126.7694612128 1
1.2%
126.7726617072 1
1.2%
126.7747422976 1
1.2%
126.7772262217 1
1.2%
126.7791051341 1
1.2%
126.7931838853 1
1.2%
126.8014125952 1
1.2%
ValueCountFrequency (%)
127.4455847953 1
1.2%
127.4455394346 1
1.2%
127.442051622 1
1.2%
127.2686362039 1
1.2%
127.2680660418 1
1.2%
127.2068978004 1
1.2%
127.2011439464 1
1.2%
127.2007546539 1
1.2%
127.1851469497 1
1.2%
127.1422876875 1
1.2%

업태구분명정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing80
Missing (%)100.0%
Memory size852.0 B

X좌표값
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
<NA>
77 
204587.893314423
 
1
185741.5
 
1
197749.906483732
 
1

Length

Max length16
Median length4
Mean length4.35
Min length4

Unique

Unique3 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 77
96.2%
204587.893314423 1
 
1.2%
185741.5 1
 
1.2%
197749.906483732 1
 
1.2%

Length

2023-12-11T06:21:20.294150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:21:20.388899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 77
96.2%
204587.893314423 1
 
1.2%
185741.5 1
 
1.2%
197749.906483732 1
 
1.2%

Y좌표값
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
<NA>
77 
488613.261273805
 
1
424082.345
 
1
433375.260797702
 
1

Length

Max length16
Median length4
Mean length4.375
Min length4

Unique

Unique3 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 77
96.2%
488613.261273805 1
 
1.2%
424082.345 1
 
1.2%
433375.260797702 1
 
1.2%

Length

2023-12-11T06:21:20.494491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:21:20.590869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 77
96.2%
488613.261273805 1
 
1.2%
424082.345 1
 
1.2%
433375.260797702 1
 
1.2%

문화체육업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
무도장업
80 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
무도장업 80
100.0%

Length

2023-12-11T06:21:20.697913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:21:20.784597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무도장업 80
100.0%

공사립구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
사립
80 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 80
100.0%

Length

2023-12-11T06:21:20.860803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:21:20.937059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 80
100.0%

보험가입여부코드
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing79
Missing (%)98.8%
Memory size292.0 B
True
 
1
(Missing)
79 
ValueCountFrequency (%)
True 1
 
1.2%
(Missing) 79
98.8%
2023-12-11T06:21:20.998763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값문화체육업종명공사립구분명보험가입여부코드
0고양시윙윙댄스스포츠20161031<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산동구 중앙로1261번길 19, 1001호 (장항동, 호수광장빌딩)경기도 고양시 일산동구 장항동 857번지1040237.658259126.772662<NA><NA><NA>무도장업사립<NA>
1고양시일산무도장20070601<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산서구 고양대로632번길 74, 2층 (일산동, 제일빌딩)경기도 고양시 일산서구 일산동 655-8번지 2층 일부<NA>37.683597126.769461<NA><NA><NA>무도장업사립<NA>
2고양시벽제19960605<NA><NA>폐업 등20080219<NA><NA><NA>경기도 고양시 덕양구 통일로768번길 12-7 (관산동)경기도 고양시 덕양구 관산동 179-2번지41280237.688514126.865971<NA><NA><NA>무도장업사립<NA>
3광명시동서 무도장20030528<NA><NA>운영중<NA><NA><NA><NA>경기도 광명시 광명로 910 (광명동)경기도 광명시 광명동 158-79번지 3층42380737.479966126.85499<NA><NA><NA>무도장업사립<NA>
4광명시광명 스포츠 아카데미20030528<NA><NA>폐업 등20061106<NA><NA><NA>경기도 광명시 오리로985번길 4 (광명동)경기도 광명시 광명동 158-811번지42385837.479344126.853424<NA><NA><NA>무도장업사립<NA>
5광명시모범 무도장20030528<NA><NA>폐업 등20060816<NA><NA><NA>경기도 광명시 오리로 976 (광명동)경기도 광명시 광명동 158-84번지42380737.479514126.854881<NA><NA><NA>무도장업사립<NA>
6광명시제일 무도학원20030528<NA><NA>폐업 등20060915<NA><NA><NA>경기도 광명시 광명로 946 (광명동)경기도 광명시 광명동 92-6번지42380637.483101126.856445<NA><NA><NA>무도장업사립<NA>
7광명시철산 무도학원20030528<NA><NA>폐업 등19991112<NA><NA><NA>경기도 광명시 오리로856번길 23 (철산동,명산빌딩 502)경기도 광명시 철산동 397번지 명산빌딩 50242383737.475689126.8693<NA><NA><NA>무도장업사립<NA>
8광명시소하 무도학원20030528<NA><NA>폐업 등20020617<NA><NA><NA>경기도 광명시 기아로6번길 6 (소하동)경기도 광명시 소하동 1242-3번지42382637.435977126.879886<NA><NA><NA>무도장업사립<NA>
9광명시한국 무도학원20030528<NA><NA>폐업 등20140107<NA><NA><NA>경기도 광명시 오리로 856-8 (철산동)경기도 광명시 철산동 411번지 그랜드 프라자 2층42383737.474879126.867735<NA><NA><NA>무도장업사립<NA>
시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값문화체육업종명공사립구분명보험가입여부코드
70의정부시유원무도장20101021<NA><NA>폐업 등20130604<NA><NA><NA>경기도 의정부시 시민로 80 (의정부동)경기도 의정부시 의정부동 494번지 센트럴타워 B1동 102호48084837.737964127.044065<NA><NA><NA>무도장업사립<NA>
71이천시국제무도장20000927<NA><NA>운영중<NA><NA><NA><NA>경기도 이천시 어재연로10번길 43, 소망빌딩 (중리동)경기도 이천시 중리동 214-7번지 소망빌딩1737437.277866127.445539<NA><NA><NA>무도장업사립<NA>
72이천시유로무도장20020607<NA><NA>폐업 등20070105<NA><NA><NA>경기도 이천시 어재연로10번길 48 (중리동)경기도 이천시 중리동 215-4번지46780037.277532127.445585<NA><NA><NA>무도장업사립<NA>
73이천시이천무도장19991228<NA><NA>폐업 등20061121<NA><NA><NA>경기도 이천시 서희로59번길 13 (창전동)경기도 이천시 창전동 156-3번지46780437.280793127.442052<NA><NA><NA>무도장업사립<NA>
74파주시태평양무도장20090810<NA><NA>운영중<NA><NA><NA><NA>경기도 파주시 금정18길 15 (금촌동,3층)경기도 파주시 금촌동 69번지 3층41301037.761256126.774742<NA><NA><NA>무도장업사립<NA>
75파주시팡팡무도장20080624<NA><NA>폐업 등20161109<NA><NA><NA>경기도 파주시 파주읍 연풍5길 28경기도 파주시 파주읍 연풍리 295-7번지41386337.828571126.838514<NA><NA><NA>무도장업사립<NA>
76포천시J당구장20160229<NA><NA>운영중<NA><NA><NA><NA>경기도 포천시 중앙로105번길 13-4, 3층 (신읍동)경기도 포천시 신읍동 54-12번지 3층1114737.896097127.200755<NA><NA><NA>무도장업사립<NA>
77포천시토지무도장20101231<NA><NA>운영중<NA><NA><NA><NA>경기도 포천시 영북면 운천로 50경기도 포천시 영북면 운천리 523-17번지48789238.091045127.268636<NA><NA><NA>무도장업사립<NA>
78포천시금호무도장20090930<NA><NA>폐업 등20120727<NA><NA><NA>경기도 포천시 신읍길 8 (신읍동,3층)경기도 포천시 신읍동 58-1번지 3층48704037.895458127.201144<NA><NA><NA>무도장업사립<NA>
79하남시킹당구장20170404<NA><NA>운영중<NA><NA><NA><NA>경기도 하남시 미사강변대로226번길 26, 3층 301호 (망월동, 미사원프라자)경기도 하남시 망월동 970-1번지 미사원프라자 3층 301호1290937.569793127.185147<NA><NA><NA>무도장업사립<NA>